Innovation and Philosophical Denial

UNIVERSITY OF CALGARY

Robert A. Este

A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

GRADUATE DIVISION OF EDUCATIONAL RESEARCH

CALGARY, ALBERTA JANUARY, 2012

395 Wellington Street 395, rue Wellington Ottawa ON K1A0N4 Ottawa ON K1A0N4 Canada Canada Your Me Voire reference ISBN: 978-0-494-83441-1

Our file Notre reference ISBN: 978-0-494-83441-1

NOTICE: AVIS: The author has granted a non L'auteur a accord^ une licence non exclusive exclusive license allowing Library and permettant d la Bibliothdque et Archives Archives Canada to reproduce, Canada de reproduire, publier, archiver, publish, archive, preserve, conserve, sauvegarder, conserver, transmettre au public communicate to the public by par telecommunication ou par Plntemet, prfiter, telecommunication or on the Internet, distribuer et vendre des theses partout dans le loan, distrbute and sell theses monde, £ des fins commerciales ou autres, sur worldwide, for commercial or non support microforme, papier, 6lectronique et/ou commercial purposes, in microform, autres formats. paper, electronic and/or any other formats.

The author retains copyright L'auteur conserve la propri6t6 du droit d'auteur ownership and moral rights in this et des droits moraux qui protege cette th6se. Ni thesis. Neither the thesis nor la th&se ni des extraits substantiels de celle-ci substantial extracts from it may be ne doivent Stre imprimis ou autrement printed or otherwise reproduced reproduits sans son autorisation. without the author's permission.

In compliance with the Canadian Conform6ment d la loi canadienne sur la Privacy Act some supporting forms protection de la vie priv6e, quelques may have been removed from this formulaires secondares ont 6t§ enlev6s de thesis. cette thdse.

While these forms may be included Bien que ces formulaires aient inclus dans in the document page count, their la pagination, il n*y aura aucun contenu removal does not represent any loss manquant. of content from the thesis. Canada Table of Contents

Table of Contents [i] Abstract 1 Prologue 6 Acknowledgements 9 Preamble 13 Chapter 1 — Backdrop with Questions 16 1.1 — Nuclear Power 16 1.2 — Supersonic Transport 20 1.3 — Summary 22 Chapter 2 — A Background to Awareness 25 2.1 — The Example of the IB1 27 2.2 — The IB! as a Complex Adaptive System 36 2.3 — The IB1 and Emergence 37 2.4 — Where is Philosophy in the Example of the IBI? 47 2.5 — Conceptual Slippage 61 Chapter 3 — The Puzzlement 64 Chapter 4 — Initial Discussion 72 4.1 — Epistemic Clarification 78 Chapter 5 — Quine and the Drawing of Inferences 89 Chapter 6— The Absence of Philosophy 109 6.1 — A 2nd Example of Absence of Philosophy in Science 111 6.2 — Reflections Stemming from the SKA 121 6.3 — Philosophy in the Pursuit of Science 131 6.4 — Discussion of Philosophical Challenges of Science 133 Chapter 7 — Absence of Philosophy in Innovation and Organizational Policy 142 7.1 — What is Innovation? 143 7.2 — What is Organizational Policy? 159 7.3 — Synthesis 164 Chapter 8 — Moving Forward 173 Chapter 9 — Understanding Denial and Delusion 180 Chapter 10 — Conclusion (Philosophy Undenied?) 203 Bibliography 208

[i] Abstract

Through ten chapters, this thesis explores and develops fundamental philosophical questions about the role of philosophy in innovation. In so doing, we examine what is taken to be a growing absence of philosophy, and then move towards identifying a potentially useful direction for revitalizing and enhancing philosophical inquiry and thought. All of this takes place against the backdrop of situating innovation in the broader context of the work of philosophy. The primary claim underpinning this thesis is that understanding more of each in the context of the other simultaneously enhances both.

The first part of this thesis provides a very brief high-level overview of two examples of innovation and the above-mentioned "forward march" that can be characterized as being reasonably complex, and, for the most part, has lived on what most would agree is (or was, during earlier times) "technology's leading edge". These examples are briefly reviewed from the perspective of the types of developments that took place to achieve them (or, at least, bring them close to fruition). In reviewing these examples, we make the observation that we find little if any explicit consideration of philosophy, or of reflective philosophical thought — and then a question: why would it be that we find the work of philosophy in our achievements (or in our attempts to reach substantial organizational, scientific, engineering, and political goals) either entirely absent or almost imperceptible?

This sets the stage for the core of this thesis: namely, an exploration of why explicit consideration of philosophical questions — having to do with rigorous thinking about presuppositions, for example — appears entirely absent from so much of our contemporary enterprise, and, especially, from so much of what we appear to aim to accomplish with what we think of as innovation.

As this core is first developed, a speculative question appears: what might have happened if either the approaches to or the steps taken in that development

1 had included philosophical considerations and explicit philosophical thought? That is, we consider the question of whether things might have turned out differently if explicit philosophical work had been a part of combined, leading edge scientific, technical, engineering, and organizational work. This question is examined through some speculative exploration of scenarios where outcomes are sketched that are plausibly different on account of what might have taken place if philosophical thought had been explicitly incorporated.

This is a difficult and highly challenging task. Serious consideration of this formative question in essence creates an argument in support of claims based on the negative example. This is akin to tacking against the wind. Rather than pointing at apparently reliable evidence of what we agree is, or what was, we are pushing ahead (some would suggest it is "pushing sideways in order to move forward") to think about what might have been. Empiricists both living and dead might spin like high speed lathes at the thought of such a prospect. Alternative histories, usually considered to have their home in fiction, can be entertaining and might even help us think more clearly about antecedent variables that may not have been previously considered; and, when focused seriously on our thinking about the future, they may occasionally help us map out plausible routes to what we think are desirable outcomes (Schwartz 1990; Brand 1992). Fiction in science and medicine, for example, is built on our capacity to invent and maintain things and concepts in our imagination that can arguably help shape our thinking of where our world will next be developed (Petersen et al 2005).

But, how can we take seriously any thinking about things — including a range of alternative processes and outcomes that quite simply did not happen — especially when our best historians and our most trusted and secure compendia of reliable information that we denote as facts about the world provide for us the clearest story, the sharpest possible picture, of what "in fact" took place? If philosophical considerations or explicit philosophical thought is not in much (if any) evidence when we explore the record of what appears to have taken place in the

2 realm of innovation, for example, how can we then defend or make use of the notion of what might have taken place if such philosophical thinking had ever occurred? This very serious challenge illustrates the utility of and reason for philosophical thinking; and, founded on innovation examples that are briefly reviewed in what follows, reflections on this sort of challenge wrap up the first part of this thesis.

Mid-portions of the thesis that follow move to a somewhat finer level of detail. This takes place in later chapters that provide overviews of two more examples of innovation environments, projects and processes in the realm of leading-edge science. They are based on the author's many years of work in both inventing and shaping, and also extensively managing two projects described. In essence, these two examples are founded on direct personal evidence and are offered here based on the argument of the strength of rationally justifiable representativeness (Cuba and Lincoln 1981). Although eyewitness testimony is often subject to serious question (Loftus 1974; Tversky and Kahneman 1977), it can nonetheless have a very strong influence on juries, for example, and if carried out rigorously to avoid errors of misinterpretation, can aid in filling out and adding value to what is generally thought to be the acquisition of a reliable and comprehensive picture. In this sense, the experiential examples are meant to add value to this thesis through the critical descriptive and interpretive methodology applied in any case study (Yin 2009) and especially based on the procedures of synthesis and interpretation of "thick description" (Geertz 1973)1.

A connection is made between the parts of the thesis that are based on these examples in the following way: the two personal work-based examples in the second section are specific to the general case that is provided in the first They thereby add to the illustrative power of the range of examples provided here. In this way, the absence of philosophical considerations or philosophical thought in these

1 The author's graduate-level study and field training in field work sociology at the University of British Columbia focused on case study methodology; the author has also taught the principles of case study metho dology in undergraduate sociology.

3 examples is further revealed. Additional reflection regarding the challenge of this absence, or, if you prefer, the puzzlement of why this might be so — is offered.

The thesis then moves into the realm of complex adaptive learning systems, the conceptual home to all the examples provided (as well as those that are included later in the document to emphasize the point). How such systems and individuals in them do or do not learn, adapt, and shape their environments to survive and thrive is explored. Against this backdrop, the reasoning we appear to carry out to do our best innovative, scientific, and organizational work is further examined. Ideas are introduced addressing why conceptual slippage — for example, mistaking one form of reasoning or one framework for another, or coming to a conclusion or ignoring important aspects of what we are dealing with — can lead to powerful philosophical denial.

In the chapters that follow, further examples of absence and therefore denial of philosophy are provided, including work and thinking in the fields of quantum mechanics and the holonic enterprise. How innovation and organizational policy are understood also adds to our understanding of the emergence of this denial. Each example reinforces the motivation to determine why philosophical denial might be so common. This leads to consideration of the reasons for denial of evidence and reason in the working of religious faith. Faith in reason and non-reason is examined.

The final part of this thesis suggests that the denial of philosophy may be a plausible indicator of slippage into non-reason, where the hard conceptual work of rigorous philosophical consideration is regarded as not only unnecessary but even threatening or just plain unknowable. Philosophical work is thereby removed from consideration. Having developed a foundation for the final argument that the denial and loss of the work of philosophy is not desirable because it limits reason, the thesis concludes by suggesting that philosophical awareness and work must be revitalized to eliminate or at least minimize denial. Additional rigorous investigation into the dynamics of philosophical denial — essentially, the pursuit of more focused

4 and practically oriented philosophical work — is necessary, and argued to be required in an absolute sense. The final statement of the thesis rests on the notion that to ignore the denial of philosophy is intellectually dishonest and morally reprehensible, and to perpetuate this denial through intellectual metadenial is fatal.

5 Prologue

We appear to have evolved a commonly held view that our products, processes and methods of thinking in science — including what we think of as innovation and the ways in which scientific work is organized and accomplished — are not only significantly different than the methods, processes, products and thinking of philosophy, but that they are vastly more preferable and desirable. Supported and nurtured by the best of our organizational efforts, we have learned well how to use innovation and science. The rapid advance and proliferation of benefits derived from the methods of science could not take place without innovation — the shaping of new ideas and things into novel products and ways of accomplishing what we see — being deeply integrated. In combination, innovation and science tangibly and reliably enrich our lives and our world (although most would admit this happens with some unanticipated outcomes and undesirable costs). Philosophy, on the other hand, appears to many to have seen better days. It seems, at best, an aging handmaiden to science, or perhaps a poor and crippled stepsister; at worst, it is more of burden, a distraction, a waste of precious time and energy. Some who see philosophy this way claim it is useless, or a pleasant gloss on the real work of science (Weinberg, 1992; Feynman 2005); and, as we shall see, some even claim the extreme view that philosophy has finally expired and is no more (Hawking and Mlodinow, 2010).

But, some think otherwise. For example, Collingwood (1936), Russell (1960) and Shapin (2008) think that the work of philosophy is, today, what it always has been — essential for exploring the locus of unsolved (or perhaps even not-yet- identified) problems. But, when contrasted with the advances of science and innovation, philosophy as an approach to challenges or problems that are unclear or not yet well defined is increasingly seen, in general, to be of little if any value. It is true that we already have plenty of challenges that are both quite specific and extremely demanding, if not overpoweringly so. Compared to the today's methods and outputs of innovation and science and the organizations that permit such

6 specific challenges to be addressed and valuable outputs to be achieved, philosophy seems to contribute little. Science and innovation and our ways of achieving their highly valued outputs and their undeniably important accomplishments are seen to be much more important and relevant than philosophical thinking, work and outputs. So the question can be posed — what, then, does philosophy do, if anything? The answer seems to be: not much, when the above comparison is made — indeed, philosophy's contribution seems almost infinitely small.

So, somehow — perhaps based primarily on what is held to be the perceived worth of output — it has turned out that the thoughts, work, impacts, and even the contemporary societal impact and role of philosophy are today valued far less than innovation and science in all their realms, as we now understand them. Science and innovation today have a powerful and measurable ROI (return on investment), and have ascended to the most prominent and favoured spot at the king's table. If it is ever remembered today, philosophy no longer has even an old, cracked bowl that has been lost somewhere outside the back door of the servants' kitchen. Although we might find reviews, reflections, summaries, and relatively meaningful stories about the earlier significance of philosophy that in its heyday helped us create, set useful directions for, and then boldly stride up the path to modernity, it seems that contemporary philosophical thought, awareness, and work, and thus the relevance of philosophy, have all but disappeared. Any work of philosophy is not in general circulation in a manner similar to the work of science and innovation.

Why would this be so? Is this a natural state of affairs — an inevitable result of how our contemporary thinking creates conceptual consistency (Ajzen 2002) while we have worked so hard to shape our modern work in the realms of science and engineering, of politics and our organizations (Kelly 1965)? Is this the course of events that must inevitably lead to the diminution and even the disappearance of philosophy from our world? Could this state of affairs have been different, and if so, would that sort of difference have made any difference (Bateson 1979)? Are science and innovation and the shaping of our organizations to move these fields forward so

7 vastly overpowering in their impacts that nothing can compete? Is this why, in the current era, philosophy is denied to the extent that, for most, it is now relegated to the status of a "forgettable footnote", something that philosophers address with other philosophers in closed-off rooms which, for the time being, the rest of us deem to be fine, as all right — just so long as whatever it is philosophers do back there doesn't interfere with the self-shaping march of science and innovation? Why, if philosophy is remembered at all, is it simply a term for many that denotes a distant and perhaps pleasant if not vaguely puzzling past — but has little if anything to do with our present goals, our achievements, our ways of thinking about and shaping the world, and especially, our ways of thinking about what is important? How should we deal with the challenge of figuring out the relationship between innovation — that which we seem to value so highly — and philosophy seems to be disappearing before our very eyes?

8 Acknowledgements

Although put into words and written by an individual, a project such as this is never really the product of just one person. So, here I will do my best to thank those who have been with me on this journey.

I have been very fortunate to receive encouragement, guidance, feedback and support from loved ones, many long-term friends, and wonderful professional colleagues who have been and still are central to my life. Even a surprisingly large number of thoughtful new acquaintances with whom I have had the good fortune to travel to faraway places, take long walks, or even wait in lineups for things as mundane as bank machines or airline security checks have all had roles to play in this project.

In conversations revolving around the focus of this thesis, each has asked interesting and even penetrating questions, provided unique insights and reflections, expressed pivotal interest, offered alternate points of view and invaluable encouragement, revealed some of their deeper puzzlements reflecting the conditions we all inevitably share, and added essential emotional and intellectual support over the many years I have spent on this project They have all freely given criticism and shared ideas in support of the countless hours of reading, thinking, reflection and writing that have comprised the work here.

Without such wonderful people providing these things, I do not think that this project would have been possible. I wish I could thank each of these people individually, but such a task would be more difficult, more complex and certainly more voluminous than this thesis! I humbly apologize to those who I can no longer remember as clearly as I would like; and at the same time, I herewith simplify to the best of my abilities, and trust that everyone 1 have known on this journey and to

9 whom I owe enormous debts of gratitude knows that I warmly thank them, and will never stop doing so.

Of course, I also wish to express my deepest appreciation to a number of very special people who will always be close, and, with their kindness and love, have made this project both possible and doable.

First, my parents, Juoko William and Sara Ellen, who very early on instilled in me a deep appreciation, a sense of wonder, and a profound respect for nature, for science and philosophy and their endless investigation, and especially for the pursuit of knowledge. My parents provided unqualified encouragement to be patient, persevere, explore, observe and discover, to ask questions and exchange ideas, reflect, and evaluate, to construct, reflect again, and reformulate. They showed me how to develop and hold ideas, to seek and investigate, how to assess, and how to learn. They were lovingly relentless with their shared goal to help me see just that one bit further, to make good use of what we know but to always push beyond established boundaries, to take intelligent risks to find whatever lay beyond the horizon, to seek and develop even more information, and especially, to pursue understanding, as best as possible, of whatever might emerge both on and off the path ahead. Throughout their lives, they consistently invited me to see, helped me learn how to learn, and to come to know so well and then critically embrace that fire in the belly. Their memory continues to show the way.

Second, my dear wife, Theresa, for her endless love and support, even when she quite rightly worried very deeply that my interwoven and sometimes erratic exploratory trajectories containing great excitement coupled with insight, discovery and success — but often interleaved with frustrations, fatigue, fear and failure — might never lead to completion. I write this today only because she has never stopped urging me focus when my mind has wandered, while at the same time always encouraging me to fly when my heart had become so heavy 1 was certain I could not She was certain that this project would definitely see the light of day, even

10 if there were many times when I was convinced, often late at night after running into some brick wall or other, that it could never happen. She may have been tempted to also think exactly the same thing — perhaps more often than I would like to think — but she never once let on. Without her, this flight would have been impossible.

Third, my students who, it turns out, are also my teachers — all the way from elementary and high school, through to graduate school and beyond, to countless other friends and professional colleagues, researchers, engineers, polymaths, and even some truly deep thinkers — all of them, ranging from those with a wide variety of special needs to the superbly gifted. Each of them, in their idiosyncratic ways, has taught and continues to teach me what it means to be "switched on" so that it will never be possible to ever again switch off; to engage genuinely in the deep and essential swirling pleasures of exploration, discovery, reflecting, doubting, questioning, and then knowing; and especially, to know and share the joys of learning, to never abandon the quest, and to keep learning how to learn. They have taught me what constitutes a good question, how to keep constructing, developing and asking new ones, how to listen carefully and go about seeking plausible answers, how to enhance their application, and how to share and encourage others to do the same. All have taught me to learn how to teach, and especially, to keep learning how to learn.

Most importantly, our number one grandson, Jadyn, who from the day he arrived has always and without any conditions whatsoever invited me to learn from him what it means to embrace life, to be fearless, brave, loving and thankful, to persevere and thrive even when the odds seem hopelessly impossible, to push forward regardless, to fail and to succeed, to learn anything at all, to find wonder in all we see and do, to understand and seek even more understanding — and especially, to love without limits. I hope that eventually 1 might achieve at least a small part of what comes so naturally to him. He has taught me what authentic living is all about, to respect and value all experience, to be courageous and thankful in the

11 face of impossible adversity, and to recognize, honour and return love when it inevitably appears. His lessons will never end.

Finally, I would be totally remiss if I neglected to thank and express sincerest appreciation to my advisor and colleague, Dr. Ian Winchester, who has, for much longer than he might have originally planned or ever thought necessary, provided consistent and extremely helpful encouragement, critical feedback and support, and open-ended freedom to think, explore and create; to all the members of my dissertation committee for their endless patience and not inconsiderable trust and understanding; and, to the Graduate Division of Educational Research and the Faculty of Graduate Studies at the University of Calgary for allowing me unparalleled flexibility to allow the admittedly difficult completion of this project while I simultaneously carried the heavy weights of serious, life-threatening illnesses and compounding health problems for both myself and my wife, coupled with attempts to make a living by continuing to partner in the ongoing invention of new science, not once, but twice — and at the same time, to explore the emergence of that science, to push for advancements in science policy, what we persist in thinking of as innovation, and especially, the philosophical underpinnings of all of this. I am grateful for the intellectual partnership and the opportunity to commence and carry out this work, which task I am quite sure will continue for the rest of my life.

12 Preamble

The pursuit of science, of innovation, and how we shape and run our organizations to promote these things can be viewed as a useful example of what we do well to achieve epistemic clarification and positive epistemic value — that is, we work hard and to the best of our abilities to clarify what we know, and in the same breath, to know what we clariiy in order to achieve our ends. All of this is based on understanding. We are not much different from our forebears in this regard— as Plato observed, we are driven to understand — the drive to understand is "in our nature".

As we have evolved and developed in scientific and philosophical realms, we seem to have come to our present status in order to build and hold what we take to be reliable and trustworthy accounts and beliefs about the objects of our attention, and thereby stand on what we conclude is the best foundation we can thereby muster. We do this with most of our other pursuits as well, as mentioned above, including science, innovation, and with our organizations, which we attempt to understand and run in accord with policy — the formalization of best mechanisms and strategies for allocating resources and achieving our goals (Downey 1982). In all these realms, the goal of epistemic clarification is to achieve what we believe to be a reliable knowledge foundation, which we then employ to hopefully optimize our decisions and improve our science, our innovations, our organizations, the outputs of our efforts, and thereby our well being. This fabric of our most reliable methods to building knowledge, understanding, and achievement is, of course, woven with the strands of what we hold to be reliable beliefs.

The evolution of science in concert with philosophy has been has been mapped by Collingwood (1960) and Russell (1996) from the time of the early Greeks to the first three decades of the 20th Century. The scientific method as we now understand it has gradually evolved as a strategy for rigorously assessing what we observe about the world, incorporating and comparing our observations with what we have

13 already learned about that world, developing and testing hypotheses to verify or disconfirm what we think we have observed and thought about that world, and through this process of clarification, developing and establishing optimally reliable explanations and theories. When we carry out rigorous investigations in this manner, this leads us to think we have acquired enhanced knowledge of the objects of our attention in particular, and to feel both reasonably secure in that knowledge while at the same time recognizing the challenges offered by those things we do not yet know, or things of which we are not yet reasonably certain. Through this process of exploration and clarification, we then establish and hold reliable beliefs about what we take to be true in the world, to the extent that this ongoing process continues to confirm and help us understand what we discover, test and learn. This approach seems to have been very successful on all fronts where it is applied, in particular in the rise of science, and this application seems universal. We have thus learned to reliably apply the scientific method to almost all that we investigate and do. Our innovations are founded on this approach to exploration and knowing, and our organizations are built to support such rigorous processes of exploration and inquiry.

The underpinnings of the pursuit of science as it is addressed here are generally applied to a wide variety of our endeavours. Indeed, it could be argued that we would not be able to successfully carry out most of what we do without the application of the methods of scientific inquiry as an expression of how we embrace, stand on and employ rigor to varying degrees of efficacy as we seek understanding of what we investigate and what we take to be more or less reliable knowledge of those things. This method is founded on epistemic clarification and thus the achievement of what we interpret as epistemic value — one might say it is founded on achieving value based on optimizing the processes of reliably knowing, and reliably knowing that we know.

Therefore it is no surprise to see major scientific projects founded on this approach to highly practical epistemic clarification, although — importantly in

14 terms of what this thesis addresses — this may not in any way be an approach that is consciously revealed or in evidence. In other words we may regularly engage in epistemic clarification to achieve what we have identified as our goals, but we may not be reflective about or aware of this mode of clarification. Regardless, it seems that any good inquiry and in particular good science is founded on this approach; conversely, bad science is not founded on this.

Against this backdrop, we now move on to Chapter 1 — an exploration of some representative examples of innovation achievements that allow us to grasp a plausible model of innovation diffusion, and begin to focus on the fundamental questions addressed in this thesis.

15 Chapter 1 - Backdrop with Questions

The first chapter of this thesis, "Backdrop with Questions", introduces two examples of relatively recent innovation achievements — or, at least, powerful forward steps that could have brought us to such visionary achievements if circumstances had not evolved the way they did. In each example briefly provided in this first chapter, the following is illuminated: [i] a vision to achieve something is identified, agreed upon, and made reasonably clear; [ii] the technologies and processes required to achieve that vision are thought about, some are brought into alignment and new ones developed, and then they are applied; [iii] the organizational constraints that define how those technologies and processes are to be researched, developed and made real are specified; and [iv] in the complex network of practical, political and organizational decisions about how to achieve the vision through such steps, at some point the project itself (or the steps being taken to achieve it) is altered for any number of reasons, and the original vision is never realized. Finally [v], any sub-benefits of steps [ii] and [iii] are extracted from the unrealized vision and differentially applied for purposes other than reaching the original vision.

1.1 Nuclear Power

In an interview regarding the science and engineering of advancing early nuclear reactor technologies and bringing the concepts into the development cycle to reach productivity quickly, Freeman Dyson is quoted by Ellerson (2009) as saying

"... [i]t's much better to make mistakes early and learn from the mistakes than to try not to have mistakes at all. If you don't allow people to make mistakes, then you don't allow anything new." This is a significant observation. Dyson's point here is that innovating in technological realms of any kind requires a freedom from overly-restrictive regulation in order to achieve the vision originally supporting the idea. With

16 projects that are highly complex with leading-edge research and development, suggests Dyson, mistakes will be made. There are risks with unanticipated consequences emerging from mistakes especially if the technologies are extremely complex and have inherent dangers, as with nuclear power. However, Dyson is suggesting an intelligent, open-minded, very well-informed balance between "pushing the envelope" on novel research in order to achieve output objectives relatively quickly and in so doing permitting the necessary research, development and innovation (RDI), versus being overly cautious and restricting and slowing down the innovation process to the extent that (potentially) the product of that process is never created and thus the benefits of the original vision are never realized. Dyson is not suggesting throwing caution to the winds; he is suggesting that we should realize innovation in new and challenging circumstances by applying the best of our intelligence to meet those challenges without being so cautious that the entire innovation process unnecessarily grinds to a halt.

Another way of thinking about what Dyson addresses here is the following: if an original vision powers an innovation process designed to bring that vision to fruition, and if the process turns out to have increasingly complex challenges and features that were not initially anticipated such that those challenges and features become more important and more powerful than the original vision, then it could be veiy useful to revisit (and hopefully reformulate) the full scenario of the original vision, what was understood and anticipated as the routes and methods that would be followed to achieve that vision, and what has now been learned about those things that were not originally anticipated. The goal of such reformulation would be to find new ways of achieving the original vision (presumably to be more in accord with the original time-line and anticipated expenditures), rather than continuing to focus exclusively on and extending the time and the new efforts now being spent to deal with new complexities (which, without conscious awareness, essentially redefine the goals and solution processes so that they replace the original vision).

Dyson's point with regard to the nuclear power question is that we now possess the necessary expertise and the scientific and technological savvy to bring

17 such products on-line in a relatively short time, and thus immediately support the original objectives of economic development and meeting other needs. He also argues that environmental and public health concerns, although real and legitimate, are subject to political manipulation that can distort public opinion about safety, for example, and this distortion can have powerful effects on strategic plans for siting, implementation, security, and use (including eventual decommissioning).

However, if we become "hamstrung" with and spend increasing amounts of time and energy on what he characterizes as overcautious regulatory overkill, both the longer-term dollar costs and the overall time delays in bringing the desired innovation into useful production mean that the project fails because wrong thinking about innovation, and its contexts, costs and benefits has taken place. As he observes, rather than taking two years of development, the time spent balloons out to 20 years or more. Dyson's argument is that the type of thinking that results in the condition of overcautious delay that permeates the original project and kills innovation and its desired outputs should be changed for the better.

One can therefore ask a number of interesting questions here: if we reflect on this example, what can we learn about improving our thinking about how to innovate more effectively? Is it simply a matter of better understanding the risks of research and development in the realm of complex technologies, some of which may include important dangers if mistakes are made? Or is it a matter of better understanding of the cost-benefit ratios of fast action versus caution in a research, development and innovation context that we feel we understand? Is an obstacle to sensible, rapid innovation that we think mistakes are to be avoided and are seen as an unacceptable cost, rather than inevitable and providing learning opportunities and therefore improvements of process and benefits of product? Or are there other aspects of the complex web of new technologies that could be more sharply and perhaps definitively developed (with unanticipated spinoff benefits?) to alter the overall technological picture and thereby improve our understanding of actual risks — essentially "carving up" the project terrain into smaller challenges and tasks that have the largest effects on how we view the entire terrain of innovation? We can

18 also ask if there are aspects of the innovation terrain, including the technologies and the political contexts, about which we are making restrictive assumptions when such assumptions are not supported by evidence. If we are dealing with unknowns (and it seems we most certainly are in the example that Dyson addresses), what are we presuming about what we don't know?

It is important that we recognize that the questions related above are both scientific / technical, and philosophical in nature. That is, they are based, on the one hand, on the technical and scientific knowledge we have acquired, about which we tend to feel quite confident and sure. They also, on the other hand, address things about which we are not quite so sure, and where our understanding is not clear; they address both what we think we understand and what we know we understand, and they are exploratory and reflective in nature.

This mixture of what we think is clear and what we are not quite so sure about defines the full challenge terrain addressed by Dyson. When faced with such a mixture (which we can suggest is the usual state of affairs in almost any context), we tend to devote our focus to those things we think we know reasonably well — in particular, the technical and the scientific. In the current era, these are the realms where we tend to have relatively secure knowledge. The more philosophical questions, ones that address more general problems that are not so well defined, are not generally addressed. From the point of view of wanting to come to the "right", "safest", "most knowledge-based" decisions about nuclear power, for example — in particular, those residing in the technical and political realms, which are usually the realms where we focus most of our thinking and energies — we tend to rely on what we already know and believe we understand. If we are faced with less well-defined questions about things that we might agree are important, we still tend to focus and rely on what we already know. The approach to decision-making regarding what to do, what sorts of risk to take, and thus the shaping of innovation direction, is therefore more aligned with what we think we know in our technical and scientific realms rather than questions about things we aren't sure of, questions that are more open-ended, questions that tend to be more philosophical in nature.

19 1.2 Supersonic Transport

The recent history of commercial supersonic transport provides a perspective into understanding innovation and philosophy that is slightly different from that of the nuclear power story illuminated by Dyson. It has a stronger emphasis on international politics although concerns, ill-informed or otherwise, over environmental and public health impacts are comparable.

The vision for viable supersonic commercial transport emerged through the 1950s as research, development and innovation in the aerospace industry, especially in France, indicated that increasingly reliable technologies of supersonic flight were at hand. Based on mid 20th Century technologies, visions of what sorts of commercial aircraft might be designed, built and put into service began to emerge. The politics of which countries could be the leading contenders in the competition to put supersonic commercial transports into the air travel market meant that the innovation capacities in necessary scientific, technical and engineering realms were identified and supported by those national governments (France, Britain, the US, and [at the time] the Soviets) already having the antecedent industry clusters capable of transforming such a vision into a viable product. Global economic conditions addressing commercial air travel from the 1960s and projected from that time into the 1990s suggested that the costs of developing and then operating a supersonic transport fleet were justifiable. We should note parenthetically that plans and projections made in the early and mid-1960s did not tend to include scenarios such as the oil crisis and the potential for critical, long-term global financial instabilities that would spill over into the 21st Century.

Against the backdrop of international competition and combined political and economically determined alliances, the combined Anglo-French aerospace industry cluster successfully met the technical and engineering design and production challenges of the day, and brought a commercial supersonic product — the Concorde — into what primarily became the trans-oceanic air travel market At the same time, the American aerospace cluster encountered a series of somewhat

20 different competitive challenges and delays in the design, environmental impact, and the emerging fuel economy realms. Where the Concorde was put into service as a technically successful product generated from what evolved into a "forced marriage" of innovation between Britain and France and entered the market as a finished product just as fuel prices began to skyrocket, the American competitive market populated by the major North American aircraft manufacturers created design and implementation delays that permitted a stronger environmental lobby to seriously question both the utility and viability of a supersonic commercial domestic aircraft The investments made by Boeing in winning the competition meant that company ran head-on into the rapidly changing circumstances of ever increasing operating costs and increasingly strident over-land environmental and public health impact criticisms and objections. The Concorde, as the successful technical product in the global competition in the commercial supersonic transport sector, ended up occupying a relatively small market niche for elite travelers and was finally removed from service after a series of accidents, and similarly increasing operational costs and maintenance issues after years of service; the American SST was never brought beyond a middle-range design stage before government support was withdrawn and the reality of an inevitably unsuccessful economic return was obvious.

The technological innovation dimension of the commercial supersonic transport saga has resulted in significant improvements to aerospace technologies beyond the original SST vision. For example, the supercritical airfoil design that was a major part of the project, and when implemented has powerful effects on low- speed control as well as high-speed (but subsonic) fuel efficiency and quiet, has now been generalized to all modern subsonic aircraft. This is a specific example of the general case of the "spin-off benefits of technological consequences of innovation resulting from an original visionary project that is, itself, unsuccessful.

Interestingly, however, in terms of the purpose of this thesis, we can return to the line of thinking about philosophical considerations brought to light with the first example about nuclear power provided in this chapter, as illuminated by Dyson. In the example of the commercial supersonic transport, we can see that a

21 complex array of technical, scientific, engineering, and political variables were at play. These variables determined the course of events over decades that moved a concept to a contextually-driven vision, the vision into the realm of what was technically feasible and politically possible, from there into the realm of financial resourcing and business plan articulation that through obvious necessity over time had to be dramatically adjusted to accommodate large-scale global political changes that completely altered the fundamental economic terms of reference that could determine the viability of the entire project, to the final range of possibilities - and actualities. This entire process over many decades determined that the original vision of commercial supersonic transport might remain bright at a relatively high level of abstraction. However, when articulated into and through the intertwined technical, scientific and political realities that evolved over the same period of time, the translation of that vision into a sustainable product became impossible - for what we can understand as combined technical and political reasons.

The present section of the thesis has very briefly described a significant innovation process that lasted many decades, cost vast sums of money, affected some of the planet's most important economic clusters and political alignments, and arguably affected millions of lives. Where, in this mix, as with the example in 1.1 of nuclear power, do we see explicit mention of the role and consequences of philosophical work? Such mention does not exist. Why is this the case?

1.3 Summary

The two brief examples in this first chapter have been provided to illustrate a plausible beginning model of innovation diffusion, where the complex of innovation processes (first identified in this chapter as steps [ii] and [iii]) is differentially adapted and modified given a complex evolving and emerging network of technical, political, and organizational constraints.

It is quite clear that in reviewing the brief accounts of these projects, at no stage of the scientific and engineering work carried out in the examples as they have been related — whether they achieved their original vision or not, or whether

22 unanticipated problems or benefits resulted — do we find any evidence for magical or wishful thinking. This, we are most certain to agree, is a very good thing: excellent science and engineering and the very hard work necessary to carry them out could never be based on magic or simply the wishes to achieve the goals of such projects. Designing, building and flying supersonic aircraft or planning for and running nuclear reactors had best not be based on what we simply hope will happen2.

The more important question that closes this chapter then becomes: in these examples, have we encountered any evidence for processes, effects or results of deliberative and explicit philosophical work? We can ask this question because neither this work and results of science and engineering nor that of philosophy contain magical or wishful thinking. Simply put, they cannot; if they did, they would not be science or philosophy. Good philosophical thought is as careful, disciplined and as rigorous as the best scientific thinking we can muster.

And yet, we do not find evidence for explicit reflective philosophical thinking or its outputs in the two examples of leading-edge scientific and technical innovation that we have briefly recounted in this first chapter. Why is this? If we agree that magical and wishful thinking are not a part of the process of scientific innovation, for example, do we have a similar clear understanding and agreement that philosophical thinking should similarly be excluded? Is philosophical thinking in some way that has not yet been articulated as silly or ill founded as wishful thinking and magical fantasy? If we understand and know why magic and wishing should not be a part of the very serious projects such as those identified here, do we

2 Dyson (2006) clearly relates a semi-autobiographical story of working as a young man on combined tactical and strategic planning for Allied bombing runs flying from England over Germany in the Second World War. In his story, not only the decisions, but entire world views of his superiors were unfortunately based on self- reinforced incorrect assumptions that could only have been founded on what was arguably very bad philosophical thinking. In Dyson's story, care and rigor were not applied to the factual information about the runs, and similarly not applied to underlying assumptions about that information, how it was achieved, and how it was used. Dyson's story describes what can be thought of as magical and wishful thinking on the part of those who were responsible for thousands of Allied airmen's lives. Dyson provides a clear example of where adherence to rigorous philosophical thought, carefully incorporated with technical, scientific and strategic military thinking, would have saved lives, reduced suffering, saved money, and potentially changed at least some outcomes of the war.

23 have a comparably clear understanding of why philosophical thinking and philosophical work should also be kept out? In focusing exclusively on the technical, political and organizational components of innovation as it relates to the advance of science and the economy, is it possible that we have committed a grievous and potentially fatal philosophical error by blinding ourselves to the importance of the work of philosophy when we engage in the innovation and work of science, engineering, and politics?

In Chapter 2, we will begin the move to explore the author's personal work experiences in leading edge science as more proximate examples of demanding and rigorous enterprise that also appears to exclude explicit philosophical work. But before we do, we can raise a question that at this stage of the thesis that can only be defined as formative, as yet having no definitive answer, namely: if we were to re think the variables contained in the technical, political and organizational mixes that have begun to help us understand the innovation process, would explicit philosophical considerations have made any difference to the outcomes of these projects? And if so, how could this happen?

Let us reflect on these formative questions and move on to Chapter 2.

24 Chapter 2 - A Background to Awareness

In the first chapter of this thesis we reviewed a range of variables in innovation based on leading-edge science that met, or did not met, their original visions and goals. Through brief recounting of their stories, we considered aspects of their technical, political, and conceptual terrain. This review has suggested that explicit philosophical thinking has generally not been a part of such innovation pursuits. In this way we can begin to consider whether philosophy appears to be regularly excluded from innovation.

The second chapter of this thesis, "A Background to Awareness", now moves to the specific and personal example of the recent creation and activation of the Institute for Biocomplexity and Informatics (IBI) at the University of Calgary. This is the author's personal experience. It is story is meant to describe the process and experience of putting a novel scientific institute together in a "classic" academic environment, and illustrates from a personal perspective that recent broad and deep experience at the leading edge of contemporary scientific investigation and innovation through the establishment of a novel scientific institute explicitly revealed nothing systematic or substantial about the philosophical underpinnings of this enterprise, or how serious consideration of philosophical issues or questions could ever have been an explicit component of the creation, implementation and growth of the IBI.

Coming to this realization based on this experience provided a strong motivation to explore why it seemed to be the case that philosophy in general or epistemic clarification in particular did not seem to be very much in evidence in the world of emerging science and innovation. This was the cause of much questioning and, indeed, some angst

25 I should point out that in beginning to ask serious questions about the place of philosophy in the realm of innovation, I was greatly inspired by Collingwood (1960) who notes,

"[b]efore the nineteenth century the more eminent and distinguished scientists at least had always to some extent philosophized about their science, as their writings testify. And inasmuch as they regarded natural science as their main work, it is reasonable to assume that these testimonies understate the extent of their philosophizing. In the nineteenth century a fashion grew up of separating natural scientists and philosophers into two professional bodies, each knowing little about the other's work and having little sympathy for it It is a bad fashion that has done harm to both sides, and on both sides there is an earnest desire to see the last of it and to bridge the gulf of misunderstanding it has created. The bridge must be begun from both ends; and I, as a member of the philosophical profession, can best begin at my end by philosophizing about what experience I have of natural science. Not being a professional scientist, I know that I am likely to make a fool of myself; but the work of bridge building must go on."

Having begun to think about the apparent absence of philosophy, and as I contemplated the possibility of "harm and bad fashion" coupled with the plausible need for bridge building between science and philosophy, I decided to explore this terrain to the best of my abilities. I therefore move forward in this thesis by relating the story of the Institute for Biocomplexity and Informatics not so much as a case study but as a review of a complex constellation of circumstances and events that caused me to puzzle ever more deeply over the bases for how we appear to think about science, innovation, organizations, and in particular, how philosophy fits into such thinking, if it does at all.

It is this story upon which I construct the later sections of this thesis that follow here, where I raise and explore what I suggest are significant philosophical questions that I hope can guide us to avoiding further harm and help to build Collingwood's bridges. This then sets the stage for practical suggestions about embracing philosophical inquiry in the worlds of emerging science, innovation, and organizations in general.

26 2.1 - The Example of the Institute for Biocomplexity and Informatics

One afternoon in the first Winter weeks of January of 2004, from my home office in the shadow of Mount Rundle in Canmore, Alberta, I gave a "cold call" to theoretical biologist Stuart A. Kauffman who was then living in Santa Fe, New Mexico. He did not know me, and I did not know him. Kauffman achieved some fame for his early work on Boolean networks, explorations of criticality, what is called "the inference problem" in Biology (attempting to infer network structure and dynamics from experimental data), and especially puzzling over problems of emergence, about how life came to be, and "what comes next". Plus, he had successfully worked in applying complex adaptive system principles to business.

Based on what I knew of his story, I invited Kauffman to visit Calgary, Alberta, to be a catalyst, the main speaker — a speaker of some interest, reputation, and perhaps even providing some gravitas — in three local venues with which I had become increasingly familiar at the time, and which had an interest in the implications of novel, leading-edge science: academe (through the University of Calgary), business (through major oil companies based in Calgary), and the arts and management (through the Banff Centre, in Banff, Alberta). The invitation was conditional upon my being able to raise sufficient funds to cover the costs of travel and accommodation, and perhaps an honorarium — but I needed Stuart Kauffman to say "sounds good" before I began soliciting funds. He did; and so began my initial task.

There was a method to my madness. Kauffman had for years contributed seminal concepts to the field of complex adaptive systems (CASs), adding much to thinking about emergence and evolution including the NK model in Biology (Kauffman and Weinberger, 1989) apparently generalizable to other fields. Indeed, two years later, he was to give the 2006 Herbert Simon award lecture entitled

27 "Emergence" at the annual International Conference on Complex Systems (ICCS) conference (NECSI, 2007).

I had been working on the germ of an idea, bubbling away in the back of my mind, an idea of connecting with a scientist of Kauffman's caliber and perhaps having that person serve as a focus for initial discussions about complex adaptive systems and their scientific, economic, and societal implications; and, if good fortune was to smile — with the addition of longer-term strategic planning, and acknowledgement of all the hard work that would entail — I thought that exposure through Kauffman to interesting ideas about complex adaptive systems (especially in Biology) might conceivably catalyze thinking among others in the Alberta venue about similar things so that new emerging science could be explored, and positive effects on the shaping of some aspects of medicine and perhaps even long-term science policy might result. I thought that this might formalize and help establish something truly new, interesting, different, useful, and even broadly beneficial in, and for, Alberta — to collaboratively lead exploration of the new field of Systems Biology.

As the last days of January 2004 winked out of existence, what that something could be was unknown. But the unknown can hold much promise. And I acted, thinking that taking risks by stepping into and exploring the unknown — proactively creating the future, on the fly — is necessary if interesting things are to be discovered, opportunities uncovered, and new achievements accomplished.

1 knew veiy well that my thinking and initial steps to initiate exploration had precedent in the complex adaptive systems literature. I had read many of Kauffman's Santa Fe Institute preprints, articles, and his books of the time — Origins of Order (1993), At Home in the Universe (1996), and Investigations (2000), for example, and along with many others by similarly thoughtful and creative people such as Prigogine (1985), Waldrop (1992), Lewin (1992), Holland (1998), and Casti (1995). I had been (and still am) very interested to learn whatever I am capable of

28 learning about complex adaptive systems and especially the very interesting place that so many initial writers in the field denote with the term "The Edge of Chaos" — posited to be a critical phase transition in state space somewhere between predictable stability or even moribund inaction on the one hand, and utter chaos on the other where, apparently, systems (which we here assume spend most of their energy to compute in order to accomplish their work) do the very best job of computation with whatever it is they compute — where "very best" can mean a variety of things, such as "most efficient", "most creative", "most productive", "most original", and "most adaptable".

It seemed highly plausible, and it was a very powerful early intuition to many, that rapid adaptation and learning and, therefore, achievement of competitive advantage and much innovation, lived on or somewhere very near this "Edge of Chaos", and that this might apply to many types of systems. Even though we must be very cautious about such things, intuition can often prove to be beneficial by pointing a possible direction for the development of good science. Even Tom Peters (1987) had started to wring a living — in fact, a very good living — out of the term which was rapidly finding its way into the management literature (Reed and Hughes, 1992) as well as much more broadly into the scientific (Strogatz, 2004); and John Brockman (2009) creatively sliced the first word out of the term, boldly claiming it to describe his creation where he could organize and distribute the thoughts and writings of some of the most creative, inventive people on the planet

What an exciting and promising place this edge appeared to be! What a challenge to learn more about and understand this phenomenon! What could we determine from studying the histories, behaviours and living actions of organisms and organizations that struggled — and evolved, failed, or succeeded to live another day — to survive and thrive, effectively partnering with other successes and on the way eliminating those who could not compete? Could we learn from the examples around us so that we, too, might live and dance more effectively on that edge (Mitchell, 1996)?

29 I dreamed of applying to organizations any underlying principles of "the very best job of (generic) computation", of exploring that critical phase transition, of living on "The Edge of Chaos", so they could become more productive, more adaptive, more innovative, less moribund, and skate along the edge but never fall into chaos. My first focus and motivation: leading-edge science in the realm of Systems Biology as an engine of societal innovation and benefit might be very well engineered and benefit strongly by closely studying and then taking such an edge into account.

This thought had come from the synthesis of a great deal of "breadth" reading I had been doing in the fields of Biology, Physics, Astronomy, Engineering, Medicine, and Computing Science — and other fields such as Economics, Management, Psychology and Anthropology. I was interested to learn what I could about what scientists, clinicians, inventors and practitioners from a wide range of fields were putting on the table in terms of new concepts, new ideas, new developments, new insights, new directions, all of them up for review. I wanted to learn about their workspace, social, intellectual, emotional and communication efforts, ways of dealing with the unfolding of emerging new science, and how they moved their knowledge products forward. I had inferred that such advances were most likely reliable indicators of what might come about in broader societal and economic contexts — and if not "what", then "where". As Steve Jobs of Apple Computer was wont to say, we might in this way have signs to "the next insanely great thing" (Wolf, 2007).

But I interpreted Job's words to apply well beyond what was to shortly emerge as his string of "iThings". I was paying close attention to writers like Christensen (2003), Christensen, Roth and Anthony (2004), Utterback (1994), Hesselbein et al (2002), and Iansiti (1998) among many others who were making interesting comments about innovation writ large (especially against the backdrop of rapidly growing technologies), what it takes to innovate more, how to do so more

30 effectively, and what problems befall organizations when they innovate or attempt to do so. The scientific research fields of Biology, Physics, Chemistry, Medicine and Computing seemed to be particularly active and fruitful, moving forward rapidly in many directions and on many broken fronts and, especially, those fronts were notably interactive — with IEEE, for example, starting a new journal on Systems Biology (IEEE, 2004) and new physical entities such as the Institute for Systems Biology (ISB) (2005) and Harvard Medical School's Systems Biology Department (2006) rapidly taking shape with good funding, good business and research plans, good equipment and facilities, and especially, the pulling together of very, very good people.

While thinking about the "Edge of Chaos", I also began thinking that, in some combinations, these vibrant fields, unfolding and labeled with increasingly flexible interdisciplinary meanings, might provide very fertile grounds for opportunity — both in terms of emerging new science itself by way of Systems Biology, and in terms of potential economic yields from the development of such new science.

I also learned of the funding agencies in the Province of Alberta. In accord with the four guiding "Provincial Priorities" in place at the time of energy and environment, health and medical technologies, agriculture and forestry, and information and communications technology (with nanotechnology as a fifth to follow shortly thereafter) (2006), such agencies received and reviewed research funding proposals from scientists, engineers, and medical specialists of all stripes here at home, or went further afield to recruit some of the planet's best and brightest to come to Alberta to establish what one might call a "critical presence" and comprehensive strategic research and action in their fields of expertise — fields that, from a the perspectives of elegant design of and impact on research, development, and economic growth, were (and are) aimed at being central to the engines of leading edge research, development, innovation, economic diversification and well-being, health and wellness, and business productivity.

31 Against the backdrop of these factors, a convergence of events unfolded. Some events were engineered locally; others were pushed forward by much larger forces. The emerging multi-faceted, interdisciplinary field of "Systems Biology" was nascent but beginning to burst at the seams, budding forth and being recognized on many university and science policy radar screens around the world, hammered out in a variety of different organizational shapes, sizes and configurations from malleable raw materials in Physics, Engineering, Biology, Chemistry, Computer Science, and Medicine. The rush to create a bold new future was on.

The small amount of funding I had been seeking materialized and, as planned, in mid-February 2004, Stuart Kauffman arrived in Calgaiy to speak about phase spaces, emergence, criticality and the frontiers of "New Biology" research in the three aforementioned venues. These talks had the desired effects, causing people to pause and reflect about this thing called complex adaptive systems, and especially how it could be seen in the emerging new field underpinning what was turning into the new science of Systems Biology. Many of the people who heard the messages and the questions wanted to know more. What did this mean? What were the implications and potential opportunities? People began to pay attention. What was possible here? Interest began to build.

As part of a longer-term strategic plan to actively create a novel research space that blended new information technologies with the emerging field of Systems Biology, one of the Alberta funding agencies, the Informatics Circle of Research Excellence (iCORE), was poised to recruit a leader in this field and fund a unique renewable 5-year program — to be a kind of catalytic "seed" mechanism for creative ideas and leading-edge research in this burgeoning field. Leadership at the University of Calgary and in the Provincial government recognized a unique opportunity to launch a truly novel project that had the potential to strengthen this important part of emerging science, research, development and innovation at the University of Calgary, and thereby carve out a leadership position on the global stage of truly important new science in and for Alberta. The necessary initial

32 alignments were made, a strategic recruitment plan was activated, and I was hired to create, shape and write the proposal in concert with Stuart Kauffman to spell out what a viable, unique, competitive, world-class Systems Biology project in Alberta would look like and could actually be.

The project name in the proposal became: "The Institute for Biocomplexity and Informatics" — a useful name in part reflecting the primary funding source as well as the requisite involvement of high-end computation to aid in solving some of the most daunting research problems appearing at the time in the emerging new Systems Biology field, problems that are best cast in the light of biocomplexity coupled with a strong computational challenge. We began to envision the new institute as being founded on bioinformatics, but this would be an institute "on steroids". An initial focus, where advanced computational tools could be applied to real and increasingly difficult and novel biological and medical problems, was the controversial field of cancer stem cells, in tandem with regenerative medicine. Over the Summer and Fall, the proposal for the new institute grew, was repeatedly refined, was submitted, and then went forward through three levels of formal review — Provincial, National, and International. Then, in the last days of November, 2004 — just shy of 10 short months after the initial project idea had first seen the light of day and Kauffman first came to speak, and just three weeks before Christmas — the project was formally approved. Five years of funding for the proposed Institute were allocated by iCORE in conjunction with commitments from the University of Calgary and small amounts from other players. Kauffman was named as the iCORE Chair in Biocomplexity and Informatics and Director of the new Institute, while I was named as the Deputy Director3.

January 01, 2005 dawned as the first official day for the Institute for Biocomplexity and Informatics at the University of Calgary. Housed at the University of Calgary, initially in one small office with a telephone and one computer, plus a

3 My role was later refined to that of Director of Operations.

33 growing plan for action and some truly radical scientific goals, we were at last real! An initial formative strategic plan for all aspects of Institute activity and growth was developed and put forward. An international network of collaborating scholars was assembled and a variety of research thrusts, ranging from theoretical to experimental to simulation, were activated at various levels of intensity. A $2 million plan for the first of three laboratories was drawn up, space allocated, cutting-edge robotic equipment for high throughput screening and computer- mediated imaging was designed, custom-built and ordered, and further rounds of combined Federal and Provincial funding were orchestrated and acquired to pay for it all.

After almost 24 months, in the early Spring of 2007, the first of the three planned IBI labs was fully equipped, outfitted, and began operations. The original research goals of the institute began to be realized. Much collaborative network building on campus, across the Province, nationally, and internationally was undertaken to raise awareness of, explore, and participate in the emerging and rapidly growing and multifaceted interdisciplinary field of Systems Biology, with the new Institute having a unique initial focus on the dynamics of cancer stem cells and investigations into regenerative medicine. The Institute for Biocomplexity and Informatics became pivotal in the initial shaping of the new Canadian Association for Systems Biology. My role as Deputy Director, along with that of Director Stuart Kauffman, focused on strategic planning, lab completion, local collaborations, recruitment of new faculty, PDFs and staff, and extensive network and relationship building. After initial explorations with many vendors, industry relations with IBM became a strong focus that lasts to this day, with the view in mind to access and participate in the development of burgeoning High Performance Computing (HPC) essential for the novel research of the Institute for Biocomplexity and Informatics and its collaborators, especially in terms of simulation of and processing of increasingly large volumes of data collected from very complex systems ranging from genetic regulatory networks in cells to quantum effects at the atomic level.

34 By the Spring of 2008, the Institute had grown to five leading full-time faculty with world-class expertise in Systems Biology, Quantum Chemistry, and Computational Biology, plus almost 20 others who occupied PDF, graduate student, lab support and administrative roles. The Institute was at that time in the process of expanding to three fully equipped labs and a computational facility that already featured a 240-node quad-core cluster, and also had extensive grid computing access. By 2008, the publication record of Institute members since inception numbered over 100 articles and conference presentations, featured in leading journals and venues in Biological, Chemical, Physical, Computational, and Science Policy fields. The strategic development and business plans of the Institute were refined and greatly enhanced to step beyond the original focal areas of cancer stem cells and regenerative medicine to include investigation into advanced cell differentiation therapy, computational biology and computational chemistry, and newly-defined emerging fields denoted as "Atoms to Cells" and "The Physics of Life", each of which presented novel scientific, technical, conceptual, and organizational challenges. Experimental results from the Institute began to show, for example, that cell types might correspond to attractors in a critical phase space, and that control of perturbations in that space could allow significant insights into the exceptionally complex terrain and specific interrelated mechanisms of cellular differentiation. Based on such work, the Institute set itself to exploring the development of therapeutic drug leads to control and steer cell fates — which in turn can be thought of as major advances in understanding the ways in which networks of genetic switches and their products, hitherto unknown or inaccessible, could be medically manipulated to positively influence health and disease.

These are significant achievements that were accomplished in the slightly more than three years from the time that the Institute was formalized. By the Spring of 2008, the Institute for Biocomplexity and Informatics was approaching a turning point — renewal for a second 5-year period was contemplated and planned. An expansion plan to 10 or more faculty, a commensurate number of PDFs, graduate students, technical support and administrative staff, and a comprehensive and

35 unique industry relationship with IBM as a potential supplier of High Performance Computing (HPC) and research involvement was sketched out Necessary laboratory and office space, experimental equipment, and additional computational facilities were featured in this plan, and faculty pursued comprehensive funding possibilities. The anticipated products of such expansion and renewal included reaching significant experimental, theoretical and simulation goals and milestones more rapidly — and, of course, developing further research outcomes and moving strongly into IP, health, and economic development realms.

2.2 - The Institute for Biocomplexitv and Informatics as a Complex Adaptive System

The IBI as an initiative at the University of Calgary had been designed, resourced and activated to generate leading edge research in Systems Biology, initially addressing the complex of variables making up genetic regulatory networks of cancer stem cells. The Institute for Biocomplexity and Informatics leveraged standard, well-established discipline-focused resources, structures and processes, and simultaneously developed novel, adaptive, increasingly productive and highly proactive exploratory configurations of research and development derived from globally emerging interdisciplines comprising the Systems Biology realm. As such, the Institute for Biocomplexity and Informatics explored and actively participated in the development of Systems Biology as a new field of science and actioned many directions and roles in integrating that developing new field into a well-established scientific institution, understood here both in terms of field of disciplines (and interdisciplines), and as a functioning agent of advanced research, change, and education — the bricks, mortar, programs and people that comprise a university.

The story provided above about how the IBI came to be and how it has evolved is an interesting complex adaptive systems case. The obvious simple reason why this claim can be made is that the Institute for Biocomplexity and Informatics as an organizational phenomenon was characterized not only by a history of instantiation and resourcing of a core idea moving into and through stages of

36 ongoing development, diversification and growth — following a path of innovation — but also a massive proliferation in the number of variables and interrelationships among those variables that, following some very simple basic design principles, by their very existence defined through an iterative process what that organization could emerge to be. This way, the new institute could determine its overall evolutionary and developmental direction, processes, and products. In other words, with initial simple constraints, the number of variables and their connections in the system we can denote as "The Institute for Biocomplexity and Informatics" is large, is complex and highly dynamic, is growing, and although many individual components can be known, and known in some detail, the full extent and nature of their richness, interactions and products, and the full system of which they are a part, is and will remain unknowable in toto. This is analogous to any system comprised of essentially unknowable numbers of elements and interrelations, where many of the elements can be understood in relative detail both individually and in classes, but how they interact and evolve at different levels of organization, at different rates and at different scales, and how emergent properties of the larger system evolve, cannot be fully known or predicted by their individual various smaller-scale behaviours. To use Kauffman's and Darwin's combined thinking, it is not possible to know in advance what will emerge from the processes of emergence, or to know with any precision how that process will take place.

2.3 - The Institute for Biocomplexity and Informatics and Emergence

At this juncture it is useful to examine the concept of emergence, as the design of the Institute for Biocomplexity and Informatics appears to revolve around enhancement of heuristic processes amongst new interdisciplines that could over the long-term hopefully be advanced and loosely-coordinated to help define the relatively new field of Systems Biology. The concept of emergence is used to describe the appearance of macro-level patterns, structures or system properties where such features are generated by the dynamical properties of and interactions among system elements and components at the organizational micro-level. The

37 term is commonly used today in this way by complexity theorists (see Holland, 1996; Waldrop, 1992) and emergence concepts are broadly utilized in economic theorizing and systems biology (see KaufFman / etal, [2000,2006,2004]), but was first addressed by the ancient Greeks (see Nicolis and Prigogine, 1989; Goldstein, 1999). It seems to be a useful term to describe both the intended overarching purpose of and operational design parameters of the Institute for Biocomplexity and Informatics, designed to seed innovation.

How can this utility be explicated? Examples of what are thought to be emergent phenomena abound and will help inform the example of the Institute for Biocomplexity and Informatics. In gross analytic terms we can easily recognize that our thinking of what constitutes an "ant hill", "hornet nest", "lizard colon/', "school offish" or "bird flock" connotes emergent dynamical properties of the unimaginably large numbers of interactions and transactions occurring among all individual members or agents of the community of interest (see Anderson, Theraulaz and Deneubourg, 2002; Eberhart et al, 2001; Jacobs, 2001). A multiscale view of this dynamic would range from the ecological system within which the community exists, to the evolution of that community, to individual members and their components, all the way to the quantum interactions among the assemblies of atoms and the subatomic particles that comprise those components. If turtles are the equivalent of emergent phenomena, then it certainly appears that it is, indeed, "turtles all the way down" (or up, as the case may be).

But we focus on our communities of interest We seek to understand their patterns, flows, functions, adaptations, and other capacities. Because we have learned so well to be reductionist in our scientific thinking, we recognize, classify, explore, represent, experiment with and simulate the relatively simple operational programs that determine individual agent behaviours in these aggregates; and, as we increasingly recognize the systems and patterns of interactions among both individual agents and aggregates, we attempt to run increasingly complex simulations of those aggregates. We have concluded that emergent properties of

38 such aggregates and their n-tuples are based on the complex dynamical interactions and interrelationships among their component parts, however we classify them. But we also recognize that we cannot predict what those emergent properties will be even with the most highly-detailed knowledge of massive numbers of individual agents, their subsets, or (at least at this time), the best of computational power to assist us with those simulations.

This is in keeping with Tasaka's (1999) observation that "something is lost when an object is reduced to its component parts". Another way of making this point is: if we analyze an individual ant down to the smallest detail (perhaps at the level of bioelectrochemical neuronal pathways and processes that comprise an individual ant's nervous system, so that we know the individual "agent ant" program) — and even if we also know that many millions of such individual ants make up what we see as the ant hill — by virtue of relying only on the detailed individual neuronal mapping which we have successfully carried out, and even when we develop and apply massively parallel processing power, we cannot then predict or know the macro-scale behaviours, features, characteristics, and capacities of the ant hill (see, Eberhard and Kennedy, 2001). In other words, standard reductionist analysis and synthesis founded on what Schwarz (2002) calls the "empirico-analytical paradigm", although undeniably helpful, will not permit a full understanding of, or prediction of the products of emergence. The only way we can know something about what may emerge is to run individual agent programs together in relatively large numbers in parallel on massively parallel systems, so that their aggregate behaviours become autocatalytic and generative — that is, so that they produce macro-scale behaviours, features, and characteristics that are not in any way written into or known in advance as a part of the micro-scale programs (see Theraulaz and Deneubourg, 2002; Holland, 1992).

Emergence has been considered an essential concept in fields of inquiry where many antecedent elements interact in novel ways to generate new consequences or phenomena, things that could not be predicted in advance by

39 virtue of what was known about the constituent parts. Emergence has therefore been commonly viewed in terms of the unfolding macro-scale dynamics of interactions among relatively large numbers of simple system components — the formative interplays among the parts and the whole that generates new features, characteristics, or behaviours that could not be known or determined beforehand, and for which we may not even now have adequate models to permit comprehensive understanding of such phenomena (see Cilliers, 2002; Gervasi and Prencipe, 2003; also noted by Este and Kauffman, 2005).

If we think of how the Institute for Biocomplexity and Informatics has been described here, we may usefully ask if it is an emergent phenomenon, or, as such a thing is sometimes called, "an emergent". If it was, how would we know? Goldstein (1999) suggests that all emergent phenomena demonstrate:

• radical novelty — that is, the phenomenon has properties not previously observed, and which could neither be predictable nor deducible from lower, micro-level components

• coherence / correlation — that is, the phenomenon has properties that maintain their identity over time, and correlate lower, micro-level components into a higher, macro-level unity

• global / macro organizational level — that is, the observed behaviour(s) of the phenomenon occurs at the macro, not the micro level

• dynamical — that is, the phenomenon is not predetermined, but arises in terms of new attractors in dynamical systems comprised of dynamically interacting components

• ostensive — that is, the phenomenon shows itself and is recognized

Goldstein also suggests that when viewed through the lenses of complexity theory, emergent phenomena also demonstrate:

• non-linearity — that is, beyond the notion of non-linear positive and negative feedback loops, they also include "small cause, large effect" non-linear events

40 • self-organization — that is, beyond the notion of simple self-regulation, they also refer to creative, self-generated behaviours that seek adaptation

• beyond equilibrium (multi-, non-, or far from equilibrium) — that is, beyond the notion of homeostasis or 'equifinality', to include amplification of random events and dissipative structures in far from equilibrium conditions

• attractors — that is, beyond simple system equilibrium, to include dynamical attractors as features of complex state spaces where concepts such as fitness landscapes successfully account for dynamical system behaviours

The above frameworks provided by Goldstein strongly illuminates the major features and characteristics of the Institute for Biocomplexity and Informatics that permitted innovation in Systems Biology to take place, both organizationally and scientifically. These reflect not only the IBI's design parameters, but also its unfolding actions and activities, engineered to uniquely advance the field of Systems Biology — where the founding core assumption has been that a solid base of consistent inventiveness coupled with knowledge in the fields comprising Systems Biology will dependably yield unknowable processes and products, leading to new knowledge and new discoveries.

Under this illumination and having closely examined the concept of emergence and emergent phenomena as a feature of complex adaptive systems, we can take the framework of theoretical characteristics of such a system and use it as a lens through which to view the Institute for Biocomplexity and Informatics. It appears clear that the IBI as an organizational phenomenon did not operate solely in accord with a linear strategic or operational plan — that is, it was not in its early stages entirely algorithmic. The Institute for Biocomplexity and Informatics was a formal creation of algorithmic mechanisms at the University of Calgary in partnership with iCORE, but one cannot step back and examine a comprehensive dynamical "wiring diagram" of the early IBI that determined what it would be, or read a full and complete itinerary of its unfolding journey as though one were following a recipe or a train schedule at the beginning of its journey. Although there was a basic architectural plan for the Institute for Biocomplexity and Informatics, it

41 was a description of very general structure and processes only, a setting of initial conditions. The initial "org chart" which most administrators seek as the organizational holy grail of explanation, control and accountability revealed very little of the complexity of relationships and interactions that connected the people, the thinking, the activities, the physical spaces, the research processes, the swirl memes and idea generation, the eureka moments and their outcomes, of the IBI.

The Institute for Biocomplexity and Informatics began as a single but very rich idea, and was transformed by strategic opportunity and vision to understand genetic regulatory networks especially of cancer stem cells into a novel entity designed to enrich and add value to the larger institution, the field of Systems Biology, and the Province of Alberta as a whole — both its people in terms of health and wellness, and its economy in terms of novel employment and diversification. As a networked complex adaptive system created to be an integral part of conjoined and much more stable and predictable entities, the IBI as described was comprised of non-linear and linear components, was both organized and self-organizing and adaptive, functioned well beyond equilibrium but depended on equilibrated elements, and featured interacting dynamical attractors on a variety of interconnected and evolving fitness landscapes. This set of claims can be supported by the evidence of how, for example, new faculty were hired based not on only how particular knowledge and skills would fill a predetermined "slot", but how such "slots" would also of necessity be defined, developed, shaped and articulated based in part on what skills and visions new faculty would bring, combined with the evolving vision and purpose of the Institute for Biocomplexity and Informatics and its efforts to both fit within and act as a major change agent in the understanding of genetic regulatory networks, and therefore the creation and evolution of Systems Biology.

This is in accord with the unknowability of the emergent dynamical multiscale structures and processes of a complex adaptive system, even where many of the details of the smaller scale system components can be relatively well known —

42 the equivalent of ensuring, for example, that budget management strings do what they are supposed to do, that coffee is always available in the lunchroom, that the bills are paid, or that there are adequate supplies of reagents in the lab. The business plan for the Institute for Biocomplexity and Informatics did indeed have standard, recognizable metrics and was comprised of definable elements, such as a budget that could be broken down into individual line items, and research and development time lines defined by goals, structures and functions, all of which could in general terms be predictably mapped and activated, and many of the smaller details of which could be intimately known — but, the patterns and flows of the emergence of those elements when the system was in action resulted from a combination of and interrelations among powerful and unpredictable blends of algorithms and heuristics, many of which were and remain unknown.

The emergence of large-scale, relatively stable features of the 1BI may have been constrained in structural and process dimensions by the overall system architecture of the host university and cast in general terms by the primary funding agency of the time (with many established and practiced hierarchical control systems and lines of authority, for example); however, the Institute for Biocomplexity and Informatics was at the beginning of its life intentionally designed, created and activated as a unique unit operating within, yet quite different from, its well-defined host framework. It was not "just another" department or faculty, but a formative interdisciplinary research entity that (although described by words that seem simple at first glance) does not to this date have a simple, clear and succinct definition that would place it in the same class as other well-institutionalized structures, processes and functions. The Institute for Biocomplexity and Informatics as a new entity was not so much a "skunk works" along the lines of the first days of ARPA (the Advanced Research Project Agency; see, Herzfeld 1998) but more like a multiply task-focused early era Aspen Institute (see, Hyman 1975) or Santa Fe Institute (see, Waldrop 1992). The initial design parameters of the IBI were intentionally not set to be the equivalent of a new department at the University of Calgary following well-established design and operational principles, but as a

43 unique "innovation engine" intended to enrich and diversify the functions and outputs of the institution's research tasks.

The initial design parameters of the Institute for Biocomplexity and Informatics intentionally imposed fewer constraints than are found in well-defined and established organizations. However, in its initial configuration, the IBI was embedded structurally and functionally in, and accountable to, its host organization, the university, and its primary fiinder, iCORE. It was then steered by multiple emerging decisions that can be seen as "loosely-coupled" more along the lines of improvisational jazz (see, Weick 1976; De Pree 1993) than strict lines of command for decision and action. Some might feel uncomfortable with a description of a system intentionally set near the edge of chaos necessitating some of what has been termed "muddling through" (see, Lindblom 1959) or dealing with "wicked problems" (see, Rittel and Webber 1973) but this seems to be quite a normal phenomenon in the realm of establishing an organizational function explicitly designed to collaboratively invent and shape something new and important — in particular, make major contributions to a new field of science — that happens to be just beyond and outside what is predictable and known.

This case therefore allows us to understand how an initial set of embryonic ideas has, through what we can think of as an organic blend of what I here call shaping pressures and opportunity selections, created a highly complex set of evolving, interdependent and interrelated investigative, research, development, information management, and product generation functions. These functions were and continue to be a three-way combination of technical (in the sense of the sciences that are here combined, plus the tools that allow both the sciences and the organization itself to exist), political (in the sense that discretionary decisions and prioritization about resource allocation determine who is to be afforded certain opportunities, all of this in relation to the organization's, others', and their own interests), and conceptual (in the sense of how well or poorly the technical and political variables are understood in relation to each other, and how all of this exists

44 in relation to what we have come to understand as emerging new science in the propositional and prescriptive knowledge contexts (see, Mokyr 1999; Kauffman, Logan, Este et al 2008; Tichy 1983).

If we think about the technical, political and conceptual classes of "shaping pressures", it is interesting to briefly categorize the extant factors of project creation, shaping, and evolution in this case — essentially, classes of variables that defined and continue to define the terrain of complex conditions, elements and processes that steer and advance the Institute for Biocomplexity and Informatics. For example, we have the fact that iCORE existed in 2004 and was poised to commit, and that Stuart Kauffman was at that time sufficiently motivated and interested to become available and chose to be involved; we have emerging decisions for action (for example, university and Provincial leadership deciding in a very short time frame to create a new entity and make funding available to make it happen — itself a radical move); and we have shaping pressures (for example, a broken front of support from components of the larger research community where Systems Biology and bioinformatics initiatives were also underway and contained in orchestrations from the university and from iCORE on the one hand, plus differential levels of interest and support from other components of the university on the other, adhering more strongly to conformational pressures). Beiner (1983) has suggestions about what factors might be at play in this sort of situation that has potential for both great advance as well as conflict, while Wolfram (2002) provides us with yet another example of an effort to break through conformity pressures; and we can usefully note that others have been down this road some considerable time before us. For example, we can recall Machiavelli (1513; 1992) who, almost 500 years ago, observed:

"... there is nothing more difficult to execute, nor more dubious of success, nor more dangerous to administer than to introduce a new system of things."

Machiavelli presaged whatThagard and Shu (2001) denote as "incommensurability" — namely, the lack of isomorphism between the elements of

45 the "old structure" and the "new structure", and therefore the assumed inability of the successful blending of the old with the new that would allow maintenance of and consistency among all conceptual relations.

Even with clear scientific and economic goals in mind and the engineering of the convergence of opportunities to make things happen, systemic change through the development of novel efforts to explore and move a field of inquiry forward is often resisted (either successfully or not) where such new things perturb that system, yet such moves are often accepted (either successfully or not) where new things enhance or add value to that system (Hesselbein and Johnson, 2002; Kawasaki and Moreno, 1999 ; Kelley, 2001; Kelly, 1998). This is where the evolutionary terrain of critical combinations of shaping pressures and opportunity selections is developed in the 3-way wrestling match among technical, the political, and conceptual variables. In the case of the IBI, the potentials remain and in fact are being broadened, and useful productivity continues to emerge. It is helpful to recall that the New Penguin Dictionary of Science (2002) defines heuristic as "(a)n intelligent trial-and-error approach as opposed to a rigid algorithmic method. Heuristics are used in computer programs which can learn from experience." The Oxford Companion to Philosophy (2002) states that an heuristic is "(c)onducive to understanding, explanation, or discovery."

Earlier in this section, I made the comment that leading-edge science might be very well engineered and benefit strongly from closely studying and then taking the ideas and models of "the edge of chaos" into account If we think this to be so, I believe that in examples like the Institute for Biocomplexity and Informatics, we can only get to and then have a hope of successfully navigating the edge of chaos to advance science in a non-incremental fashion by standing on the excellent algorithmic foundation we have created, and use that as a solid base from which to launch the best exploratory heuristics we can muster — to engage in the best

46 abductive reasoning4 possible (see, Peirce 1934; Harman 1965; Aliseda 2006; Thagard and Shelly, 1997; Magnani 2000], and at the same time be driven by the call to maintain perspective (see, Schwartz 1991). The Institute for Biocomplexity and Informatics — still very young, still in its early formative stages, still very much an "emergent" — is a very good example of precisely this exercise.

2.4 - Where is Philosophy in the Example of the Institute for Biocomplexity and Informatics?

In doing this sort of thing I believe we are creating the future epistemology of science (see, Cetina 1999). However, in terms of the goals of this thesis that aim to address the denial of philosophy, I am not sure that an example such as that of the Institute for Biocomplexity and Informatics does anything more substantial than illuminate the fact that we do not know nor might we even be aware of what we are doing in the epistemic realm, and that in this example virtually nothing was in evidence having to do with explicit discussion about how the IBI as an agent of institutional and scientific change could play, plays or has played a role in exploration or explication of the philosophy of science, or how considerations of the philosophy of science played into how the Institute for Biocomplexity and Informatics was first conceptualized and then actualized. This was the core of commencement of my deep personal awareness of the absence of philosophical questioning or reflection in what was ostensibly an innovative, leading-edge scientific enterprise. This growing awareness was surprising given the relative significance of the scientific and medical goals being undertaken in the IBI, the complexity of organizational arrangements that were engineered to render it possible, the apparent valuation of the enterprise in terms of budget and in

4 "Abductive reasoning accepts a conclusion based on the grounds that it explains the available evidence. The terms was introduced by Charles Sanders Peirce to describe an inference pattern sometimes called 'hypothesis' or 'inference to the best explanation.'" (The Oxford Companion to Philosophy 2nd ed, pi). Also see Papineau (1996) and Harman (1965, Philosophical Review, 74, The inference to the best explanation), "In general, there will be several hypotheses, which might explain the evidence, so one must be able to reject all such alternative hypotheses before one is warranted in making the inference. Thus one infers, from the premise that a given hypothesis would provide a 'better' explanation for the evidence than would any other hypothesis, to the conclusion that the given hypothesis is true."

47 particular the commitment of large portions of people's professional and personal lives, and the extent and nature of what could be accomplished if the scientific and medical goals of the Institute for Biocomplexity and Informatics were to be achieved. I began to think very seriously about why philosophical questions and considerations were not in any way a palpable part of this enterprise.

So, the first question: how did I know to do this? It seems in the personal example of co-creating and building the Institute for Biocomplexity and Informatics that I encountered some initial indicators that a very interesting new terrain did indeed lay ahead, and I saw that its exploration was not only promising, but essential. If the goals of the institute could be met just partially as it was developed, significant advances in both the understanding and clinical realm of human health and disease would be possible. To use the idea of how we see indicators of actions that may be afoot in our nearby environment, and where we might wish to go to learn, survive and thrive, one might say that I saw fresh tracks along the riverbank and decided to act on what I inferred from them. Let us look back at the starting point of this history to determine where and how I moved into a realm of philosophical questioning and awareness.

Through three decades of reflective practical experience, professional practice, and scholarly pursuit, I found that I shared a number of assumptions with many others (ranging from academic and professional colleagues to business associates and students, from family members to casual acquaintances and even to some authors) about innovation and science; and, through much of this time, I found myself to be more or less confident of and secure with many of these assumptions. They seemed to consistently explain experience (and even the history and interpretations of others' experience); and holding them — essentially as lenses through which to view the terrain of unfolding and emerging new things and new science — appeared to permit knowing what innovation and new science were believed to be, and how to act appropriately in relation to them: after all, it seemed that most others both felt and believed the same as I did. I knew of conformity

48 enforcement but did not think that what I was experiencing had much to do with that I learned to handily use the aphorism of "if the only tool you have is a hammer, everything starts to look like a nail", and even turned its nested questions inwards. However, I did not initially feel much in the way of motivational stirrings to clear away the conceptual overburden to the extent that my absolute presuppositions could be revealed.

For example, 1 was aware of well-studied problems that are reported to emerge with "groupthink" (Janis, 1972), but happily, the shared beliefs about innovation and science in which I was immersed when the first glimmers of thought about the potential of an Institute for Biocomplexity and Informatics appeared did not seem to give evidence of those problems. Writings about science policy, for instance — even those that acknowledged "fuzziness" and "unanticipated outcomes" — appeared to assume a kind of "perfect rationality" on the part of policy actors along the lines of what is so well-liked and powerfully advanced by traditional market economists (see, Friedman 1990). I read organizational management stories about prescriptive strategies and tactics that could be employed by almost anyone to guard against poor performance or mediocrity (at best) or wastefulness and destruction (at worst): that is, we could benefit greatly from "a whack on the side of the head" (von Oech 1992), "thinking outside the box" (Eisner 2005), employing "TRIZ" (Altshuller 2005), or "managing at the edge of chaos" (Peters 1987). I read "first blush" stories about complexity (Hall 1991; Lewin 1992); these suggested that dynamics having to do with complex adaptive systems could be transferred back into the human organizational realm (Auyang 1998; Lissack 1999), and as is the case with much of memetic infection due to the undeniable attractiveness of the snake-oil side of the concepts to which we are attracted to support choices about what we think we know, became common currency powering a growing interdisciplinary feeding frenzy, where leading proponents nipped off fresh buds and supped, refreshed and energized, "at the edge of chaos".

49 This was an exciting state of affairs, and at the time I did not yet find myself asking deeply reflective questions about why these things appeared to be so. Articles and communiques of all kinds proliferated having to do with complexity and complex systems, and how challenging it was to formalize and to understand; yet these same writings suggested how natural it was to apply to common, everyday experience as well as the challenges of understanding systems of systems previously thought to be intractable. New ideas about complex organizations and systems of all types were being developed, and what appeared to be fundamental new knowledge about complexity and complex adaptive systems was being rapidly generated. This new knowledge could describe and explain and perhaps even create a new scientific discipline that would allow us to understand so much that had previously been unknown, and apparently unknowable, about the networks, systems and dynamics that seemed to comprise so much of our complex world. Prescriptions about how to think about these new ideas, implicit in the articles and communiques, flowed freely; prescriptions about how to influence and affect organizations and systems of many different kinds and how to improve their "yields" (especially knowledge yields related to them) were issued at a rapid rate by well-recognized and memorable men (not too many women) whose excitement about their claims often overshadowed almost everything else, although it was assumed to be the case that, being very good scientists, they all adhered to the highest standards and evidence and rigor.

Based on such reassurance, I became convinced that it was possible to safely assume that following such prescriptions would permit all desirable results from a multiplicity of efforts to generate new ideas, new things, come up with new solutions, make more money, solve apparently intractable problems, train better and smarter people, create indispensable new knowledge and "a culture of innovation", and especially, strengthen and add to the national economy. With such prescriptions, it became evident that what was being addressed, and the suggested methods for solution, were virtually certain. Naysayers were nowhere to be seen. Algorithms for success were ours to be had at every turn, and the benefits from them lay well within reach! Like the siren's call, this was terribly exciting and more

50 than promising. Questions I might have had about how to innovate, how to create benefits, how to make innovation happen, and even what constituted this thing called innovation, all had the potential to be answered!

However, over a relatively short time, the excitement began to fade. I quickly realized that the circularity of holding and reinforcing shared assumptions maintained against a backdrop of parallel assumptions about exercising necessary and sufficient critical thinking was, indeed, a problem; and, I realized, it was a crucial problem at that. My thinking about finding the keys to innovation in emerging science through the study of complex adaptive systems had been my initial motivation to pursue studies in this area; but, I found that holding and reinforcing these assumptions did not lead to satisfactory knowledge of what innovation is, how it (or, whatever we think innovation might be) can be enhanced, or (in the case of where my interests were at the time focused) how new science emerges. Assumptions such as those identified in the previous paragraphs continue to be held by many to this day, of course, and coupled with this, innovation and new science appear to continue; but, it remained unclear (and remains so to this day) if I, or anyone else for that matter, actually understood, or understands, what we claimed or assumed to be so.

What 1 am here calling "core shared assumptions" about innovation and emerging science included the following: that we know what innovation is (or, put less positively, that what we think we know about innovation is good enough — it is adequate — so there is no need to know any more than we do); that innovation — whatever it might be, or whatever it is that we are referring to with the term "innovation" — consistently appears to generate some levels of enhanced economic outputs for the benefit of all or at least those who are the engineered beneficiaries, and is therefore obviously desirable, even if we don't understand what innovation is, or how it accomplishes what we think it does; and, the "good enough" of both incremental and radical innovation adequately explains how we create new emerging science — the assumption being that we don't need to have full, complete

51 and comprehensive understanding just so long as it does what we generally hope that it should. By holding such shared core assumptions (even if they are remarkably similar to a house of cards) over a period of time, as long as the house did not collapse, it became possible to successfully claim expert and reliable knowledge about innovation, the emergence of new science, and the relationship between the two. Articles were published, conferences attended, and news items even appeared in the popular press. Holding and reinforcing such assumptions allowed the claim to be sustained, and sustaining the claim allowed the assumptions to be reinforced. An engine of self-perpetuating claims and assumptions was created and was itself sustained. In this state, on one day, a new prescription could be written about what to do to create innovation; if the system receiving the prescription could not make use of it, or use it well, a further prescription on the day following was all that was needed. Fine-tuning what to do seems a perfectly fine thing if the assumption is made that what is being fine-tuned is understood even if it isn't, and if no deep questions are ever asked about the system that has been created to support the assumptions.

A surprise can be detected here, and I am reporting the surprise in this story about my own growing awareness because I suspect it was pivotal to my shifting focus from wishing to study innovation and the emergence of new science, to realizing that to address these things I must first explore the field of epistemic clarification in order to know, or at least hope to know, what I was aiming to address.

I began to think about how to carry out such clarification. First it became apparent that the condition and state of affairs described above does not generally seem by many to be problem or a suspicious nest of circular reasoning; rather, it seems to be (and, I think, we prefer to think of this as) a description of a well- integrated system of beliefs about whatever the object of our attention happens to be — even if some system components are acknowledged to be poorly understood. A doctor might prescribe one treatment, and then another if the first doesn't seem to

52 work; the range of possible causes for observed symptoms or evidence upon which to base a diagnosis are founded on assumptions about which species is being examined and treated. In other words, innovations we generate and emerging science at which we arrive through what we understand to be the best available rigorous means are to be fundamentally trusted. This, after all, seems to be the best we can do; and, it even seems that from time to time we do better. Standing on this ground, the assumptions we have held to get to that ground are repeatedly verified and generally understood as being correct We therefore believe that what we assume is correct, and in so doing, we do not find ourselves very often investigating the deepest of our basic assumptions about these things.

In such an exercise, we also want to believe that our beliefs are founded on exploring and then knowing systems that are logical and integrated and therefore reasonably predictable, and thus almost always capable of description by algorithm. We tend to approach the objects of our study — even if they confront us with such intractable complexity that we call them "hairballs" or, as one wag recently termed them, "the ridiculome" (Kaern 2005) — as not being fundamentally chaotic and random and therefore unpredictable and incapable of algorithmic description. We approach such very difficult problems with the assumption that they are amenable to simplification, reduction, and thus representative systematic understanding. We also want to believe that our beliefs about these things are, themselves, an example of such an integrated, predictable system that can, if required, be described by laws, for example. It is a very hard problem to understand something that is chaotic — but integrated systems, we think and tend to believe, are systems that can be reduced to the point of being understood with necessary and sufficient effort, clarity, discipline, and focus; and, the basis of understanding is knowledge, as complete and integrated as possible, and logic that is tight and unassailable. Such understanding reveals reliable knowledge of system components, their behaviours, and the relationships among them — and can even lead us to discover fundamental laws about such systems.

53 We tend therefore to think of the most valuable pursuits of knowledge as being, quite literally, systematic; and that that knowledge so derived, too, must be systematic. After all, given our history (essentially since Galileo, as outlined by Russell [1996] and Collingwood [I960]) of seeking, seeking to understand, and then successfully illuminating integrated systems, the behaviours of the components of those systems, and today even more about systems of systems, our shared core epistemology about things like science (indeed, what we hold to be true about science itself) is that, all around us — and even we — are comprised of integrated systems, and systems of systems that we continue to explore, discover, and understand. Through science and its systematics we can identify, reduce and even eliminate magic; we can see, understand and grasp the elements of the world and the extent and nature of their relationships; we can understand and stand in awe of our world, and reach out to see and perhaps even move to distant worlds beyond.

This is heady stuff. It is no wonder that in the history of science there has been a long battle between magical and scientific thinking, still underway in some quarters. We can also happily report that our history demonstrates systematic scientific activity to be, in general, a successful enterprise. The basis for such thinking is the rigorous exploration and establishment of a system of assumptions that lead us to reliable knowledge. In other words, the state of holding assumptions and claims provides reliable evidence of the rigorous pursuit of understanding of systems.

At this point I came to recognize that I was confidently standing on a strong historical foundation of the logic of rigorous scientific inquiry, discovery, definition, and presumed integration. The unspoken assumption was that we were dealing with systems — linear ones palpable through reductionist science, and complex non-linear ones beginning to be illuminated by the ongoing study of whole systems and their parts. But no matter how comfortable I felt about my claims, or how integrated and well thought-out I believed my shared assumptions about such systems to be, I continued to return to a question — a sure sign that the state of

54 affairs was not satisfactory, even if I was not entirely sure why; in holding core shared assumptions and making what appear to be logically integrated claims, the question came down to the following: did I in fact understand the objects of those assumptions and claims, and what I could hold on to as their interrelationships? 1 began to reflect on other questions: how would I know whether I had achieved understanding, or did not? Would I have any idea of what "understanding" might be? What types of thinking should I pursue to approach such questions of knowing?

I reflected on my environment of colleagues and what they claimed to believe and think about their assumptions. Although I could feel secure with what I had embraced as my assumptions and was warmly reinforced by others holding what appeared to be the same or similar assumptions, although I thought that those assumptions did in fact permit me to engage in what appeared to be meaningful and rewarding intellectual, economic and emotional exchanges and pursuits about innovation and emerging new science, and although I could make decisions and take actions yielding consequences that appeared to demonstrate and confirm a logical and perhaps even desirable causal relationship between those decisions and consequences, I found that being simply confident and secure, and reassured and reinforced by colleagues, was inadequate. The answers to my questions continued to be "I am not sure; I don't know". I could not say that I understood innovation and whatever constituted its relationship to emerging science.

A short while ago, while going over some of the references I have used for this thesis, I had a powerful insight Like the familiar ingredients we find in the fridge and to which we return to combine into a good homemade soup, these references have been frequently visited, discussed, contemplated, and digested. They feel now more like parts of a comfortable and extended conversation with old friends than anything else. As 1 again reviewed what they had to say — "Does science need philosophy?" (Murcho 2006), "Philosophy and the front line of science" (Pernu 2008), "Reshaping Reason" (McCumber 2005), "Re-engineering Philosophy for Limited Beings" (Wimsat 2007), plus a host of others — I realized that before me

55 were ingredients that brought me to the following: in general, we all like to know what is going on around us, and, in particular, what will end up happening. But it had never fully dawned on me in quite the way it did on that morning just how impatient and even desperate we can be (and often are) for assurances, if not promising signs of predictability and even what we think could be certain, both about what we are doing and what will both confront us in and define the future. This realization was a new window into the dynamics of what seems to be our shared goal of wanting to be as sure as possible that we know what is going on, and what will happen in the next second, the next quarter, and maybe even the next century.

Of course there's nothing wrong with knowing what is going on, wishing to be reasonably sure about aspects of the future, and having predictability to the extent that we can engineer such things in whatever realms we happen to find ourselves. It can be plausibly argued that our ancestors most likely evolved these behaviours and the mental capacities to go with them as essential survival skills. I suspect we are here because these sorts of things worked reasonably well for our predecessors; they have been passed down to us and improved upon, at least somewhat, to allow us to reach today. Without them, we'd never be able to develop, use or understand any kinds of rules or patterns, recipes or formulae, instructions or assembly guides, or feel secure with predictable behaviours and optimally dependable systems — we would have nothing algorithmic and would, therefore, not know algorithms. It is very difficult to envision a world without some degree of patterned predictability and what are then reasonable expectations based on the algorithms we develop to understand and predict those patterns, just as it is not easy to envision a world without any predictability at all: we appear to live in a world with an interactive, changeable and dynamic mixture of the two. We can best describe this type of system as complex and adaptive. It is also a system that learns from its experiences and by extension necessarily has a memory, a recall function, and the ability to use its memory as a source of recursive input that can be blended

56 with ongoing experience for the purposes of analysis, evaluation and synthesis that allows us to achieve comparative, reformulative and adaptive outcomes.

Thinking this way about the "learning" function of uncertainty (non- algorithmic processes) in complex adaptive systems in the context of and in relation to our apparent need to find more predictability and certainty (algorithmic processes) may be very useful. We may plausibly describe the necessary and sufficient conditions for the success (e.g., survival) of all complex adaptive systems in terms of the relative longevity of a dynamic, integrated5 balance of blended certainty and uncertainty that supports learning in that system. Lack of success (e.g., non-survival) would be described by a state of affairs that is not dynamic but frozen and/or not blended or balanced (that is, not correlated nor recursively functional, and/or without positive and negative feedback among components and actions); or, conversely, a state of affairs that is chaotic with nothing that we would be able to refer to as structure or memory whatsoever. From this it is not a great stretch to suggest that only with such a mixture of integrated dynamic predictability and unpredictability, recursively supporting system learning, do we have the successful abilities to create, solve, invent and evolve. This, in turn, describes in general terms a complex adaptive system; and thus, by extension, an ecology of complex adaptive systems.

When it comes to what we think of as innovation and the pushing of boundaries for enhanced adaptability and proactivity, our species may entertain expectations and hopes and develop and make good use of the algorithms we create, but it seems we very much need to understand the role of and wisely move away from a narrow focus on predictability. These would be part of the necessary and sufficient action conditions to support the above-mentioned integration. We cannot be driven by any desperation or impatience for a solution having the characteristic

5 "Integrated" may be shorthand for "having system components and actions that are loosely correlated, iteratively causal, variously founded on capacities to reliably store and accurately recall information, and characterized by intertwined positive and negative feedback".

57 of some certainty (such as learning, or reaching the goal of integration); to successfully achieve this, we must move into the unknown where the environment, writ large, is almost guaranteed to be non-algorithmic. Some would add that we need to be very deliberative in all of this, and shouldn't rush. The argument here is: integration (and by extension, the learning that is necessary to support integration) takes time. It isn't possible to push the river.

Therefore it seems that we need to make good use of what we already know as a useful foundation, seek out and embrace the opportunities, challenges and flexibility offered by the uncertainties of what we do not know, and move forward by not denying new things or our awareness of them, and at the same time not desperately hanging what we take as answers, plausible or not, around our necks. We may find that our claims of having found the desired integration in our complex system serve not as badges of discovery, achievement and solution, but as millstones, the masses and limits of which may prevent any further useful exploration of the balanced dynamical integration of certainty and uncertainty, and thus severely restrict learning.

The main point here isn't particularly new — it sounds similar to the exhortation, which in at least the past decade has become the tired old adage, to move and think "outside the box", as previously mentioned. But the insight about this point — more a question, really — has to do with the philosophical foundations of what we unconsciously do, presumably to be safe from or at least reduce the perceived or anticipated risks of moving away from what we think of as certain: I think this is where we encounter a very important point of choice. At this point we can explore the unknown with all attendant risks of unintended outcomes and promises for what is desired. It seems we need to acknowledge that the exploration of the unknown might even lead to changing our beliefs. This is risky stuff. If we know how to "intelligently take risks" to explore the unknown which by definition is uncertain, we can enhance our chances of benefit But at the same time we can increase our chances of either damage or failure.

58 To avoid either or both less desirable of these outcomes, we can of course at this point choose to not explore these possibilities. If we make the choice to not explore, we do not expose ourselves to a new range of experiences. But if we choose to experience nothing new, we have the potential of falling into denial and thus not even knowing that this has taken or is taking place.

My claim at this point, therefore, is this: our sense of security and comfort with what we believe to be the desired predictability is rooted not only in what we believe to be reliable knowing as we develop and follow life's algorithms that for the most part bring us to what we intend (a reasonably healthy thing), but unfortunately is also based on the denial of uncertainty or perhaps the denial of what will turn out to be counter to what we had wished in the first place. This, in sum, restricts and even shuts off the opportunities offered by exploration — which I here claim isn't quite so healthy. The reason for characterizing the denial of uncertainty (or, the denial of opportunity to explore and enhance what we know) as unhealthy is that such denial severely limits or even eliminates possibilities, options and choices. Such denial is the self-imposition of limits on what we take to be knowledge, and the concurrent restriction of action and thought to limit learning. An integrated part of this claim is that it seems we are not generally willing to take much action that we interpret as stepping outside of our known algorithms, thereby risking what we believe to be our security and comfort in what we have come to hold as what we take to be justified true belief (Gettier 1963).

What we think of as denial is not uncommon. It is useful, for example, to note that recently, in the more popular press, denial has been addressed and explored at least to an introductory level (Carey 2007), and Ariely (2008) has attempted to illuminate the terrain of predictable irrationality. Denial presents serious challenges in the realms of medicine and public health (Nature Medicine 2006) and group behavior (Janis 1972; Surowieki 2005) A system of beliefs powered by and based on denial of exploration, and therefore a restricted flow of new information, presents

59 serious problems for learning, understanding and adaptation. Why would we choose to restrict our learning, when learning seems to be the basis for achieving understanding and, therefore, the core of adaptability and the engine of proactivity?

More questions began to emerge. What would be the mechanisms, the philosophical implications, and any plausible evolutionary advantage for the existence, reinforcement and perpetuation of denial? I realized I was beginning to think about what might be thought of as the interlocked dynamics of epistemic clarification and epistemic denial, and, especially, the relationship between the two.

These thoughts reminded me of Philip Armour, the computer scientist who writes about how we approach the task of writing computer code (Armour, 2000). Writing code is one of those things that is an attempt to achieve, or at least maximize, algorithmic certainty — and Armour correctly suggests this is not simple or easy. Although writing code can be readily done, it is clear that one really ought not write code that doesn't work! He argues that the challenges of writing good code are not merely technical. Although highly skilled and gifted programmers can focus their energies and efforts in apparently superhuman ways to accomplish exceptionally complex and demanding code-writing tasks, we run into problems aiming at algorithmic certainty because we tend to forget that the product of writing computer code is not the code itself, but the knowledge we create to understand and then make use of the code in the ways we had originally intended. In other words, the goal of writing code is not the code itself, but the consequences of the applications of that code. When we forget the real purpose of writing computer code and focus entirely on developing algorithmic perfection, we write code for code's sake and for the sake of coding, not for understanding and then using the code in the best ways possible. As confirmed by those who have been in the field for decades (Goebel 2006) we fall in love with the code and the act of coding, and forget what the algorithm is for. There is no question that one can be very good at writing code qua code. But this is the equivalent of the "W5" problem — working extremely hard to clearly identify and drill down into the details of the who, what, where and when

60 (the W4), and paying very little if any attention to the fifth "W" — the "why". Of course we realize that we need to do very, very well with regard to the "W4" [Wilson, no date). This tends to be so is any realm we care to examine. We require and work hard to develop exquisitely crafted and sharply refined technical knowledge and skills; we simply could not achieve what we aim to do — write excellent code, or push the boundaries on science and engineering to successfully build devices such as the Large Hadron Collider or the Square Kilometre Array, for example — without them. But without the fifth "W", we do not think well, or at all, about using the excellent code in the way we intended. We forget the deeper reasons for doing what we do.

2.5 - Conceptual Slippage

I claim we are engaged in denial when this takes place. As I have suggested elsewhere (Este 2007) this "conceptual slippage" is a serious problem because, being so enamored with the process of coding and the perfection of code, we find we don't even know that we don't know -- and this is where we can be certain (if you will pardon my use of the term) that anyone who suggests we don't know what we're talking about doesn't know what they're talking about!

This is understood to be a worldview of intentional obscurantism, known in some places as "proud ignorance". I think there's a strong parallel here for a better understanding of innovation in general — that is, standing on what we know (or at least think we know), and then pushing the boundaries and building into what we don't (at least not yet).

No one likes to think that they might be proudly ignorant. It is no surprise that most people don't like to talk about this possibility very much, and commonly become annoyed and even angry when the question is raised, especially if it persists. This causes me to wonder if we actually can think about this prospect in any deep

61 fashion, when we do think about it, in the most productive of ways. I am optimistic and would like to think that we have the possibility of doing so. This has a direct parallel in the realm of innovation where, in general, people claim that we simply need more of it, and don't tend to think much further than that — we don't need to know what it is, really — we just need more. We just need to do more "innovation things", and perhaps do those things faster and better; we have confidence that whatever we do will then produce more of it. Policy specialists are "certain" about how to go about creating policies and the policy processes that generate policies and generate a range of outcomes, and similarly those who are specialists in innovation are "certain" about advancing what they think is innovation, and especially about pushing and pulling various policy levers to get more of it, adjusting this and fine- tuning that to get to what they think is an optimal state of affairs. But, contrary to their claims of understanding and being able to make use of policy and innovation mechanisms, they don't talk a great deal about the knowledge required to understand and then make use of policy or the policy process in the way we intend, or how it might be that comprehensively understanding innovation might make us better at innovating, rather than simply trying to get more of the same. We become very skilled and knowledgeable about how to push certain levers, turn certain dials, write certain code — but that may be all we end up doing well.

As I gave more extensive thought to having worked so hard to collaboratively build a novel scientific enterprise, I felt uncomfortable about not being able to adequately answer some of my beginning questions about shared assumptions. I began to think that what I had thought was a solid foundation for an innovative scientific enterprise such as the IB1 might actually be founded on serious philosophical questions that had fallen victim to considerable conceptual slippage, that this might not be generally known, and that we might not even be aware that important aspects of building new science were not addressed. At the same time, as I began to think about how and why we appear to delimit our thinking that we do in our efforts to carry out and accomplish many complex things, I realized in ways that I hadn't realized previously that not pursuing what we are unsure about appears to

62 be the main reason why, in the policy realm, so many policies have unintended outcomes (that is, the code might work some of the time but doesn't do all the things you had hoped; it may do nothing close to what you had hoped; it may disrupt or destroy what you already have; or, it may do nothing at all). I think this is why innovation as we tend to think about it today has primarily to do with "valorization" and "return on investment", and very little if anything with the knowledge that we create (and need to create) to understand as many dimensions as possible of this thing we call innovation. Philosophical considerations that could help us with such challenges are left unaddressed.

In the following section of this thesis I will delve more deeply into why we would find ourselves in such a situation, and what we might do to clarify and perhaps even improve it. At this point of attempting to grasp and understand at least some initial parts of philosophical denial, 1 now step into exploring the first stage of "the puzzlement."

63 Chapter 3 - The Puzzlement

In the previous chapter the personal story of the creation and establishment of the IB1 was relayed, and some reflection occurred about the apparent absence of philosophical thought or deliberation in the range of innovations that were put into place having to do with emergence and setting the conditions for the development of leading-edge science. The absence of philosophical pursuit in the example of the Institute for Biocomplexity and Informatics that was presaged with the brief review of Dyson's comments on nuclear power and the story of the supersonic transport now motivates a shift in focus from innovation and emerging science to the an exploration of how and why it might be that neither consideration nor the apparent work of philosophy seemed to be in evidence. This is indeed a puzzlement Here the story changes to an examination of how we think and how we know.

We misplace our keys, check everywhere we can think and even retrace our steps, but can't find them for love or money. We step out onto the deck after breakfast, look to the West and, sure enough, the mountains that we were expecting to see are still there. The clouds obscure the view the following day, but the day after that when it is clear and sunny again, we see that the mountains are where we saw them the last time. And one late afternoon as you nap in your favorite chair in your quiet study at the back of the house, a playing card — lef s say it's a Joker — flies out of the open window of a passing car on the street where children in the back seat are playing some card game or other. The card is picked up by a gust of wind and by pure chance blows straight up into a narrow crack in the soffit of the exterior living room wall of your house, and you will never, ever know it is there. You move to another city and many years later that house is torn down, the card finds its way into a landfill, and it is buried for a very long time, eventually disintegrating into its constituent parts.

There are times when we know what and where things are, there are other times that we don't. Sometimes we are surprised by things that we had no idea

64 would appear. And massive tracts of the universe, the world, our fellows' worlds, and even the vast majority of our minds will most likely remain forever unknown to us.

The Johari Window (Luft and Ingham 1955) is a useful and interesting conceptual device6. It permits us to frame and think about what we know we know, what we know that others don't, hint at what we know we don't know, and suggest that we have no idea about what we don't know. It allows us to think about moving the differentiations among these parts. The differentiations are arguably useful when we are confronted with experiences and events that tend to make up large parts of our challenging times — that is, sometimes it can be a very good thing indeed to be reminded, or remind ourselves, of what we can reasonably grasp and hope to accomplish, versus those things that might present more difficulty, or to be reminded that there most likely are things that could be important to us but may never be on our radar.

This differentiation seems fairly straightforward from most perspectives, and may even seem painfully obvious, but the constellation of ideas that comprise those things that can be differentiated by applying the idea of the Johari Window can sometimes be difficult to use, or put into words. Therefore such ideas can be difficult to contemplate or then translate into decisions and actions. In 2002, United States Secretary of Defense Donald Rumsfeld attempted to explain to the press a framework describing intelligence challenges faced by the G. W. Bush administration — this had to do with navigating the political terrain of intelligence and counter-intelligence, the known and the unknown (Rumsfeld 2002). His words describe challenges that are faced by us all: "There are known knowns," he said. "These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don't know. But," he said, "there are also

6 The Johari Window is a conceptual framework used in organizational and management circles as well as counseling psychology that provides a visual representation of four discrete spaces that identify what we know we know, what we are aware that we don't yet know, what others know but we don't, and what no one knows.

65 unknown unknowns. There are things we don't know we don't know." This set of statements is difficult to listen to when spoken by Rumsfeld — some might suggest this is on account of the context of delivery (a somewhat charged press conference), or even how the messenger has been perceived by some of the audience. But the statements are also difficult because what Rumsfeld describes is, indeed, a challenging terrain — somewhat useful to think about from time to time; but, like the Johari Window, not easy to consistently and regularly apply.

Based on the description of how 1 began to frame questions about why philosophy did not seem to be in evidence in so much of what I had undertaken to create, build, and implement by way of the IB1,1 next examine aspects of what we know and don't know about philosophy, how we think about philosophy and, from this, where and how philosophy appears to fit and work in various aspects of our world today. The approach taken to carry out this examination rests, in part, on thinking about the Johari Window and other aspects of belief, conviction, delusion and denial. Other conceptual tools and devices are used for this exploration as well. This thesis is thus a pursuit of epistemic clarification and, as Alston suggests (2005), has to do with the enhancement of reason.

Let us start by thinking of this "window" as having shutters. We know what shutters are for. They can be used to block the view and shut out the light. That is, in dynamic terms, we can think of how shutters would work in all four quadrants of the Johari Window — what they would prevent us from seeing or knowing that we could see; who would open and close those shutters, and for what reasons and to what ends; what would they prevent from being illuminated when closed and what they would illuminate and allow to shine through when open. If such shutters are now in place where we don't know that we don't know, obviously those shutters wouldn't make any difference. There is nothing to see or be illuminated, regardless, and there would be no way for us to know that. But if shutters are employed in the quadrants where, ostensibly, we can indeed see or the light can shine in — the result is that things would remain in the dark. In such circumstances, information

66 about what is, is denied. Here we are faced with questions about why shuttering would occur, who would be interested in doing the shuttering and for what reasons, and what we might most usefully do to understand these things and know when such shuttering is desirable, or not

These comments allow us focus on the topic of this thesis, so let us come to its basic claims: [i] that the explicit consideration of philosophy is largely absent from what humans do because we are collectively engaged in the denial of philosophy (where the view of philosophy could be clear and illuminating, it is either moved to the quadrant where we cannot see it; or, where we once could, it is now shuttered); [ii], that this shuttering denial, or at least portions of it, can be inferred from observations of how we do and do not engage in epistemic deliberation and clarification (that is, we can make this observation in situations where we seek epistemic clarification but find that we cannot discern either the task or the focus; or, we are entirely unaware of either; or both); and [iii], that in both cases this denial is dysfunctional (that is, if we were afforded a clear view of philosophy and its illumination, we could see and make use of it; and, presumably, use it well).

Against the backdrop of the introductory story of the Institute for Biocomplexity and Informatics, the explication carried out in this thesis is delimited to four very broad realms of human activity. As such, this explication is an introduction only — these are baby steps, if you will. Adult strides on this terrain will take a great deal more work and must wait for space, time and effort that are somewhere in the future. Much further work remains to be done in the realm of philosophical denial.

The first three realms explicated here are predicated on rational inquiry and the value of what we take to be reliable evidence to help us shape and act in ways we think appropriate to our views of the world: [i] how we support and steer what we think of as the advance of leading-edge science (this is the realm of scientific

67 thinking and activity that appears to have been very productive over the past few hundred years, in particular since Newton, and is focused in this thesis by consideration of one of humankind's current major scientific enterprises); [ii] how we develop and diffuse for general use new ideas and things [this is what we more often than not denote as "innovation", focused in this thesis by consideration of how we have tended to conceptualize and apply what we think we mean by this term); and [iii], how we generate and maintain relative stability and efficiency and yet encourage some capacity for a reasonable degree of adaptability of our organizations (this is what we tend to denote as "organizational policy and the policy process", focused in this thesis by consideration of systems of governance, decision-making and advisement as we currently know them, both by their functions and their peculiarities). The fourth realm explored near the conclusion of this thesis, religion and faith, is predicated primarily on tradition that includes the discounting of reason and evidence as they are considered in the aforementioned three realms, and depends heavily on suspension if not elimination of critical thought and inquiry that challenges such belief structures. In all four realms, questions about the role of philosophy in terms of epistemic clarification and philosophical analysis are pursued.

So, here, we illuminate and explore the current circumstance: that identifying, enhancing and dealing with philosophical aspects of the above- mentioned realms of human endeavour, especially the first three having to do with the apparent dedication to epistemic reasoning, commitment to what we consider to be evidence, and the pursuit of rational clarification, appears to present difficult challenges of a variety of types.

Indeed, we see here that philosophical pursuits and what we might think of as "the work of philosophy", especially epistemic clarification, are essentially peripheral to all four above-mentioned realms of endeavour, and are today almost universally marginalized if not ignored. The backdrop of major scientific and engineering accomplishments, and the story of the Institute for Biocomplexity and

68 Informatics with all its complexity and significance was the point of origin for this way of thinking about innovation in a real leading-edge scientific enterprise where philosophy, in particular epistemic clarification, was simply not in evidence. This is in line with the shutters I suggest can be in place, and the questions asked with regard to the shutters can be asked here. However, without moving to the fourth realm of human endeavour where critical thought and epistemic clarification are explicitly denied outright, the general absence of philosophy in what are taken to be our most important pursuits today, where what we think of as rational pursuit and the uncompromised consideration of evidence are paramount, is a puzzling if not a troubling circumstance. My first sense of this came by reflecting generally over major accomplishments and then with the specific experience of the Institute for Biocomplexity and Informatics; here suggest that this is especially the case in the challenges that increasingly confront us as a species. This circumstance presents us with many questions that I move to explore in this the following sections of this thesis.

I claim here that we commonly encounter, live with, and may not even be aware of what I take to be combined conceptual and practical obstacles to epistemic clarification; and, therefore, we do not in general understand or even see the need for philosophical work that could overcome such obstacles. If we ever do think about it, we assume such work has no value — and why this might be so is a core question of this thesis. In addition, I suspect that any potential awareness of the need for philosophical work to overcome such obstacles is, sadly, regularly submerged and handily held under the surface by what I will here call "the pretender" of the fourth realm of human endeavour — religion and faith — which has, unfortunately, emerged in common contemporary thinking to be unthinkingly conflated and more or less isomorphic with what has been denoted as philosophy. This is a very unfortunate turn of events and suggests that neither is well understood; but, if we take a step back and think that this could be the case, it is increasingly less of a surprise that major challenges in science and engineering in general, and a specific leading-edge enterprise such as the IBI would provide no

69 evidence for consideration of philosophical questions or conscious steps to enhance epistemic clarity. And, to conflate philosophy, religion and faith in such a manner is to severely reduce the strength and usefulness of philosophy in general and epistemic clarification in particular; unfortunately, this also adds strength to the delusional aspects of religion and faith and, I suspect, leaves us vulnerable to poor reason based on unexamined assumptions and presuppositions. This situation leaves a very serious void in our conceptual terrain, which, instead of being inclusive, rigorous, reflective, thorough and comprehensive, is as a result fragmented and supportive only of highly delimited thinking and action. What I am considering here to be a threat to rational pursuit and epistemic clarity may be most clearly visible from this perspective. I suggest here that we are not generally aware of the size or complexity of such a situation, nor are we equipped to deal well with or even recognize its philosophical challenges. This is a very serious state of affairs.

As this thesis continues, I delve into questions of why this circumstance might be, and why it appears to be increasingly normative. I suggest that, collectively, we are immersed in ongoing philosophical denial and the simultaneous denial of the value of philosophical work, that such denial and meta-denial appears to have the strong potential of being infinitely self-reinforcing, that this infinite regress of denial of philosophy has the potential to be very damaging, and that in the current era and in the conditions of pervasive absence of philosophy we generally may not be aware of this at all (this therefore suggests that the posited denial has been and continues to be successful); and especially, that under such conditions epistemic clarification as a prime example of philosophical work is guaranteed to be almost impossible. If what I am describing here could in fact be so, this would have serious delimiting effects on our best of intentions and what we think is our best thinking about innovation and our organizations within which we aim to rise to the height of scientific advance and all that we hope comes with it As a useful example, I also briefly explore the idea that delusional thinking as it appears in religious faith may have more to do with this situation than first meets the eye, protestations of innocence from various quarters notwithstanding.

70 I develop the idea that this state of affairs having to do with the denial of philosophy may be increasingly normative, and that this is not healthy or productive for any of the three above-mentioned realms of human endeavour in particular. This may be so even for the fourth (where I suspect even more very serious philosophical work must very soon be done). I suggest that the circumstance of philosophical denial presents us with an extremely serious problem that may, over time, prove to be even more serious than it now seems. I suspect that without philosophical intervention it may, indeed, eventually be fatal.

In sum, the following sections of this thesis explore and provide additional examples of what I claim to be the puzzling and very troubling denial of philosophy. This thesis then develops some plausible directions for possibly improving this state of affairs. I focus my exploration primarily on the current era.

71 Chapter 4 - Initial Discussion

We can utilize the conceptual tool provided by the Johari Window by thinking of what is in the portion of the window where we know that we know — and it appears that part is essentially bursting at the seams, for there is a great deal there that we did not know previously. We might even think that because we know so much and continue to discover and know more, that portion of the window is really all that matters. It is the case that there is a great deal more to explore, and portions of the window model allow us to see where the advance of science explores what we do not yet know. But how we decide to do these things does more than add to what we know.

The technologies we invent, deploy, utilize and diffuse through our societies in the pursuit of knowledge have powerful effects on what we learn and how we learn it As integral components of our data and information terrain, our technologies affect and even define the shape, extent and nature of our what and how we know — our ideas, our concepts, our families and social groups, or work, our relationships, and our societies (Norman 1993; Thompson 2003; Tufte 2006; Carr 2008; McLuhan 1964; Burke 1999; Fogg 1998; 2002). New technologies stemming from emerging science clearly power entrepreneurship and adaptive responses to innovation pressures (Helft 2011; Norman 2004).

An examination of innovations and technologies that we have developed over time provides for us an exquisite window into the stepwise progression not just of the tangled proliferating web of knowledge, innovations and technologies themselves, but an equally important window into how we have attempted to deal with these technologies and thus come to define our world. I will not enumerate humankind's vast and far-reaching technological, engineering and scientific achievements (although I would invite the reader to contemplate what we have achieved in approximately the past 1500 years; for a particularly useful overview, see, Murray 2003). Rather, I would here focus on the current era, as the purpose of

72 this thesis is not to review human accomplishment generally but to pay particular attention to the growth of emerging science especially in the modern era in order to illuminate the role of philosophy in our world. With this focus we can immediately realize that especially given the Internet and computer-mediated tools such as modern web-based search engines, reasonably accurate information about our achievements is readily available in almost all areas of endeavour and at many levels of detail. The lists and compendia of innovations and technologies available to us today could be thought of as never-ending, and the degrees of effectiveness and impact of these technologies, their vast interconnectedness and their profoundly intertwined interactions are evidently so complex and comprised of so many variables as to be essentially incomprehensible (again, the "ridiculome").

We can note the highlights — for example, drawing plausible cause and effect relationship links for example among the bicycle, the airfoil, and the internal combustion engine against the backdrop of plausible economic advantage to allow us to see the path of innovation that lead us to Orville and Wilbur Wright's launch of humankind into powered, controllable flight (Kauffman 2005) — but we must be content to know that such highlights represent only the most influential or high- profile inventions, prototypes, processes, products, and their various diffusing effects that take place on a vast networked terrain of technical, social, and political variables that play into the emergence of all innovation (see, Schumpeter 2008; Rogers 1983; Fagerberg et al 2005). Where in an earlier hunter-gatherer world defined by basic survival our ancestors might have learned how to treat and harden fortuitously found natural stone with heat, and then chipped, shaped and sharpened more durable knives and axeheads, or fashioned (ishhooks from fragments of bone; where our more recent forebears may have in relative terms rapidly evolved modern human intelligence as a natural consequence of a topsy-turvey and precipitously changing climate (Calvin 1998; 2002), today — built on what really are only a few centuries of increasingly dense, diverse and concentrated massively proliferating advances in science and technology unprecedented in the short history of homo sapiens — we have recently invented things like high-performance and

73 cloud computing, autonomously intelligent search engines, and devices such as massively advanced particle colliders and radiotelescopes of such investigative power to extend both our senses and cognitive capacities that the most likely thing that will ever threaten us is our augmented selves (except, of course, for truly catastrophic events such as Torino scale "8" encounters with errant asteroids and such like) (Morrison etal 2004; Hildebrand 2009). The lists of our achievements are now "classically" known. For an overview of these things we need only to visit our local library. They include milestone innovations such as the lever and screw, concrete, the library, parliamentary governance, currency, the telescope and microscope, the printing press, the loom, the rifle, the steam engine, steel, calculus, the bicycle, the automobile, the airplane, radio and television, the transistor, antibiotics, nuclear power, the computer, manned and unmanned space travel — the paltry list provided here is of course far from complete and is not being introduced here to be any more comprehensive than it is. There is no denying, however, that what humankind has been able to achieve in a very short time is indeed quite amazing (Davis and Myer 1999; Gleick 1999).

And the science we develop, much of which is expressed through the technological innovations we create and facilitated through the organizations and their capacities that we have been able to invent and engineer, therefore have a very powerful role in shaping what we think about and how we define our world.

It would be difficult today to think that anyone on the planet would hold the view that our globally networked ways of life are not driven in a multiplicity of ways or untouched by the proliferation of our complex and sophisticated modern technologies. But how do we actually engage in defining, knowing, and understanding our world, and thus live our lives in any comprehensive way in this emerging terrain of vast technological advance, penetration and diffusion? This may at first consideration not seem like a question that is worth much of our attention or time. After all — although we are not fending off predators, roaming the savannah to find water or nourishment, finding basic shelter, or raising our young in precisely

74 the same ways our ancestors did — we are extremely busy living our modern lives and surviving in the unprecedented complexities of the modern world, a world of our own creation. We are, indeed, still "keeping the wolf from the door", and given the products of our inventiveness and propensity to make more and better tools — and let us not forget that we tend to make tools that can achieve even relatively high levels of autonomy to help us make even more and better tools — we are today loaded down with massive volumes of facts, huge quantities of information that is useful, plus vast amounts of data leading to incomprehensible information that we can only think of as garbage (Postman, 1994), and the relentless demands of making our livings in the modern world.

As William Gibson observed (1994), we fell from the trees not that long ago, and the only thing that has fundamentally changed is that we are now faced with survival in a world almost entirely of our own invention, not one of nature. Unlike our ancestors, we are today not concerned so much with sharp-eyed predators that stalk us from the bushes, but about things much more vast in their impact such as global warming, potential pandemics, pollution, economic collapse and recovery, health care, identity theft, and the ageing population of which we are all a part — to name just seven societal elements that would for the most part have been almost entirely unfamiliar and greatly surprising as issues of deep concern to our grandparents, let alone our forebears of a hundred thousand years ago.

But let us address the question of what all of this means — let us pause for a moment to think about how, today, we deal with "being in the world". Being concerned about or spending time on exploring the meaning of or defining our world and our place in it does not seem to be a high priority for many if not most; the world presents us with many other priorities that seem much more proximate and important if not critical, and our contemporary environment no longer provides much comfort from "the wisdom of the elders" or from religious frameworks that in the past seem to have traditionally provided overarching meaning for almost all

75 members of society about our place in the world — a framework upon which to hang our personal or societal ideologies, our politics, and even our cosmologies.

Having now been socialized primarily as homo economicus, in this day and age we tend to work under the assumption that our world is simply here, whether we reflect upon it or not, and whether we like it or not Our world provides us with more than any one person or even any one civilization could conceivably worry about or deal with in terms of problems, challenges and benefits and things that must be done; and, depending on circumstance, great numbers of opportunities abound in almost all realms. As a species, today we have increasingly more useful and high-quality tools, more things, more information and meta-information, and more "stuff than we have ever had, individually or collectively — and it seems we remain on a path to even more of the same, with no end in sight And today we have enough trouble attempting to live our lives in the modern world as it is without having to think about it any more deeply than we already do. How could it be that thinking about our world, or our place in it, in any deep way, has any place in the modern era when we are relentlessly bombarded with, immersed in, overloaded by, challenged with, and must deal with so much that consumes so much of our time and energy and is almost impossible to comprehend in any comprehensive way?

It's hard enough just figuring out what to do to get along as best as we can and play our individual roles to survive and hopefully prosper and advance in our business, our university, or town or city, or in our country. Indeed, in parallel with these comments, a recent editorial in Nature suggests that we are so strongly focused on science that we regularly ignore other serious concerns (Nature editorial, 2011). So, if we are ever seriously faced with the question: "what is the meaning of all of this?" — most tend to leave that for someone else to worry about. And now, here it is: we have it, provided with what we can interpret as either absolute cynicism or the deepest of Zen-like clarity — as Douglas Adams wryly posited in his trilogy (2002) now some decades ago, perhaps the best we really can hope to do is accept Deep Thought's ultimate reductionist answer, the ultimate

76 "macro" of 42. Anything with more detail, meaning, utility, or import is not and will not be accessible to us. We'll never get there. It's unattainable, at least in anyone's lifetime in this day and age.

We have some interesting indicators that support the claims made in the above paragraphs. I would like to spend some time briefly exploring them before delving into the main course of this thesis. This introductory exploration will provide what I think is a very useful foundation to examine into the core of this thesis.

First, allow me to focus on very broadly- and commonly-used presentation software utilized in our computerized world of today. I here identify PowerPoint ®, but could as easily identify Keynote ®, or any other graphical slide presentation software. This type of software is extensively used to allow someone to create a slide show of information to be shown to an audience. Presentation software provides a useful multi-media communication platform with an emphasis on visual information. Frequently used in education dissemination or decision-making meetings in the realms of business, politics, the military, public service, or academe, the software has considerable utility. By incorporating a wide range and variety of colours, text and sounds, and visual images and movie clips into the slides of a presentation — such features themselves often "borrowed" from other "information integration" sources, such as the Internet, or from other digital devices such as cameras or computer graphics programs — any topic can be presented at various levels of detail, complexity, clarity, and accuracy. If carefully designed and implemented, a presentation making use of this type of software can clearly and accurately present extremely useful information that can be used to emphasize an argument or point of view, to support and shape the drawing of particular conclusions, to present facts in support of one decision or another, or to introduce options for deliberation. Like any other information technologies, presentation software can have intended as well as unintended effects. The software installation packages tend to emphasize the software's effectiveness, and ease of use and

77 upgrading. Interestingly, the software packages make veiy little mention of how the use of the software might affect the very ways of thinking carried out by the people who receive information conveyed by it and who make use of it This latter topic has emerged only as presentation software has diffused into broad general use and people have begun to think about the software's effects on thinking — on the way people shape and hold their views on particular subjects or their views about the world in general (Tufte 1983; 1990; 1997), (Bumiller 2010). In this way, presentation software can be thought of as filters — and as shutters — shaping what is known. Presentation software is just one example of how filters work on today's Johari windows. This idea allows us to move to an examination of epistemic clarification.

4.1 - Epistemic Clarification

Epistemic clarification addresses the exploration of reasons why, and plausible mental processes by which, we establish and hold our beliefs and worldviews (NECSI 2007). These beliefs and worldviews are built on, as well as components of, our epistemic frameworks, or what we hold as relatively stable yet evolving constructs (Kelly 1963). These are the things that are shaped by the Johari windows of our world. Our worldviews and beliefs are constructed, learned, established, revised and refined throughout our lives (Nersessian 1995; Magnani and Nersessian 2002; Collingwood [Martin, ed] 1998). Epistemic clarification also has to do with how people adapt their beliefs and frameworks to the challenges presented by new information that impacts those beliefs (Kuhn, 1962; Nola and Sankey 2001; Collingwood 1933). Such clarification also has to do with the extent and nature of the types of information that present such challenges, and our own capacities for responding to them. Included in these capacities are the extent to which the "filtering" of such information and consequent adaptation occurs (consciously, or unconsciously, or in combination, or nor not at all) and how we deal with errors or misapprehensions that occur by virtue of these adaptation and belief systems, as well as the consequences of both ongoing estimation, validation and

78 errors. Epistemic clarification drills down to the foundation of what we hold to be true and predictable, and examines how we go about building and modifying our epistemic frameworks to accommodate both a changing environment and changes to other aspects of the frameworks themselves. With epistemic clarification we establish a full framework of our beliefs, and thus the basis of what we take to be our reality, although this framework may never be complete (Collingwood, 1960). Commitment to the well-established components of this framework is not easy to change (Machiavelli 1513; 1992) but — depending on circumstances — change it we do, and, I would suggest, change it we must Epistemic clarification therefore has to do with the enhancement of reason; here I am aiming to increase the possibility of such enhancement in the contexts of the emergence and understanding of science, innovation, and organizational policy.

Epistemic clarification has been the purpose of the work of historians and philosophers such as Collingwood (1933) and Rubinoff (1970). In chapter 4 of this thesis I do not take an historical approach but instead explore epistemic clarification by delimiting my focus to the development, emergence and application of what we can think of as "new science". Although the results of this thesis may be generally applicable to many others of our endeavours, I choose to delimit this exploration because my most recent professional experiences are rooted in the realm of such emerging "new science" and are thus most readily accessible for examination, reflection, and reporting.

It has been my experience that working in the context of and framing and actualizing "new science" provides many good opportunities for examining the dynamics of epistemic clarification, for this is the realm within which scientists and those who support and work within this science, by virtue of their own work or the work of others, adjust and change their world views and thus their expectations, ways of framing and asking questions, and methods of searching for answers to and evaluating their work that results from those questions. I think the perspective

79 afforded by my work provides a unique vantage point for what we might call an "epistemic evaluation."

In this thesis I provide context and background but I do not relate this information as historical. Rather, I recount formative personal and professional experiences that began in 2004 with exciting and deeply important scientific questions in Systems Biology, and more recently in Space Imaging Sciences — the two realms of "new science" in which 1 have been and remain intimately involved. These experiences have taken place at the University of Calgary.

As my background and training are not in fields of biology, or physics and astronomy, my daily work over the past six years has not been done as a scientist specializing in either scientific realm. This should be quite apparent from the description of my experience with the IBI provided in Chapter 1 of this thesis. Instead, my work in these two fields has been and is still characterized by extensive involvement in answering unique science program design, development, and articulation challenges — determining, resourcing, building, and shaping the "containers", if you like, for these new science initiatives, and, at the same time, exploring the realm of long-term science policy as the context within which such development and design has taken and continues to take place. My work therefore concerns the technical, political, and conceptual components of the policy process (Tichy 1983; Downey and Este 1984) that determine how jurisdictions and their constituent elements (the scientists, their partners, and their teams as actors in the "new science" environment, the faculties, departments, and universities within which they work, the funding agencies that provide resources, and the governments that support them, for example) work together and interact in what we can best characterize as a loosely-coupled system. This can feature much of the aforementioned muddling through to build awareness of and commitments to future science direction, the technical realm that permits the work of new science to take place to be articulated by that direction, the allocation of resources and other

80 enabling moves that power the actual scientific research, and the balancing of multiple interrelated and often competing priorities.

In seeking to extend the boundaries of scientific knowledge in the two burgeoning fields of new science to which I refer in this thesis — Systems Biology and Space Imaging Sciences — my work has also included novel combinations of and investigations into scientific theoiy, experiment and simulation, the interface of these things with the development of exploration and advanced and emerging computational tools and ways of organizing, communicating about, managing and supporting such scientific work.

To the present day, these complex experiences in a dynamic and fluid strategic policy development and articulation environment have necessarily brought me to reflect deeply on the exploration, inventiveness and innovation capacities that power the emergence of science. This includes the architecting of science policy that both drives and permits this emergence to take place, and — most importantly for the purposes of this thesis — the underlying philosophical terrain that underpins the emergence of science.

On this terrain I am presenting raw materials for what 1 hope will be the useful exploration of the epistemology of emerging new science where I hope to bring new light to bear on how we might think most productively and act most usefully in relation to the epistemic concerns I uncover and illuminate here. I am primarily interested in the epistemic concerns and thus the philosophical terrain of emerging new science because there does not appear to be a clear or meaningful link between the technical and political aspects of new science (and thus the new science itself) and the philosophical foundations of that science; and, as I have intimated earlier, in my experience explicit consideration of philosophical questions or epistemic clarification do not appear to exist. It has been my experience that if the philosophical terrain of emerging new science is ever brought to any clear or meaningful level of awareness by any of the active scientific, technical, or political

81 actors involved in that science, that awareness is extinguished very rapidly indeed. I think the closest we can come today to such explicit consideration can be found in some writings of leading edge scientists who have already accomplished significant parts of their technical scientific work and now seem to have had some time to engage in reflection and write about these things (see Kauffman 2008; Gell-Mann 1995; Smolin 2006; Hofsteder and Dennett 2001; Dyson 2002; Hofstedterl999). And, it is the case that we have very good representations from philosophers of science who address epistemic concerns having to do with things such as what counts as evidence what is the scientific method (Popper 2002), what is scientific discovery, how scientists go about changing their major frames of reference for their work (Nickles 2002; Carr 2011), and how do we wrestle and derive theory from data.

However, it is my concern that such efforts, as noteworthy, helpful and significant as they might be, do not as a rule appear to deeply and effectively reach into the larger-scale "practical translation" tasks of epistemic clarification generally, especially at the "front lines" of emerging new science and its organizational support structures — that is, they have few if any obvious, notable, significant or systematic effects on either the day-to-day workings of the emergence of science, or the policy systems that shape that emergence. The action of science in terms of the method and technologies of authentic scientific investigation, and the policies and politics of resourcing that action — what 1 tend to call the "wheels on the ground" aspect of science — appears for the most part to be quite removed and take place at a considerable distance from the epistemology of science. 1 have deep concerns that what I observe in the realm of emerging science, and innovation and organizational policy as they are related to that science, are increasingly disconnected and moving away from philosophical understanding, philosophical work, and epistemic clarity. I fear this view is consistent where Collingwood (1960) leaves off in "The Idea of Nature". I am concerned about the denial of philosophy generally.

82 I recognize that such a perceived disconnect and imbalance between maximized technical and political developments in science policy discussion and action on the one hand, and minimized discussion and action regarding the epistemology of science on the other, may simply be a "normal" phenomenon of the terrain of the emergence of new science and science policy generally, where philosophical questions and concerns are not regularly considered to be of a high priority and therefore gain little if any currency. In other words, if considerations of philosophy in the realm of "science on the ground" are evolving to be increasingly on the wane to the extent that they are virtually non-existent, it should come as no surprise that experience would bear that out. We can conclude, then, that my working experience has provided solid evidence for an absence of philosophy in the realms of emerging science, innovation, and policy having to do with organizations that support these things. My question at this point, though, has three facets: [i] why would this be "normally the case; [ii] if the epistemology of science was to have a more prominent profile in the shaping of science policy, could this then allow us to hope for improvements in the outputs of science policy and the emergence of new science; and [iii] is the example from science, innovation and policy and indicator of a deeper problem of general philosophical denial?

If some of the most articulate leading scientists of the present and recent eras appear to have little notable positive effect on, or express apparent need for, the epistemology of the emergence of science generally (and here I am referring directly to Hawking and Mlodinow [2010] who claim outright that philosophy is dead, to Weinberg [1992] who claims that philosophy is a pleasant gloss the real work of science, and to Feynman [2005] who argued that philosophy was useless), what is the extent and nature of any philosophical concerns that actually do appear or are revealed, and how are they dealt with? How do we know that they actually are authentic philosophical concerns? Today, the term "philosophy" appears in briefing documents, industry white papers, and official government reports, often under the authorship of individuals such as political actors in the science policy field (Carr 2011) and Science Advisors to Prime Ministers and Presidents (Carty 2005a; 2005b)

83 — but interestingly, the term seems to be exclusively employed to denote quite specific policy "attitudes" or "approaches" that reflect the evolution or holding of values about such things as global warming or interdisciplinarity (Holdren, 2008). The term "philosophy" does not appear have any explicit connection, couched in terms that could be utilized for purposes of reflection and debate, for example, to the epistemology of science that might be of interest or concern. These observations are the foundation for my deeper concerns about the denial of philosophy.

Noteworthy here is the notion that the term "epistemology" does not appear frequently if ever in common scientific or political vocabularies, and the term "philosophy" is now being explicitly utilized in the current era in a way quite different than the way it appears to have been employed in the days of Russell, for example, who articulated clear distinctions, and both conceptual and practical similarities, between what the term would mean in the practical science policy world as illuminated by philosophers of science, versus those who are solely involved in the technical and political realms of new science policy. This suggests that scientists and their working scientific colleagues who are spearheading and actually carrying out the difficult work of new science, the administrators who are managing the organizations supporting this scientific exploration, the industry partners who co-develop and supply so many of the necessary tools and resources to cariy out the scientific exploration, and the politicians and policy analysts who create and shape the environment within which the academic, partner, and governmental organizations operate, are, by virtue of the complex tasks they carry out, re-shaping a "working" definition of the word "philosophy". They are steering away and maintaining a considerable distance from the serious and difficult work of epistemological clarification, and are instead emphasizing the interwoven technical and political strands of science policy.

This phenomenon is not new (see Este 2007) but is, 1 think, increasingly worrisome when taken in the context of today's complex evolving science policy, which classically would be defined by making use of a traditional policy process

84 model in technical, political, and conceptual terms. This phenomenon provides, I think, incontrovertible evidence for a systematic long-term process of the erosion and eventual loss of the original meaning of words that have previously been used to denote complex constellations of challenging concepts that require the hard and rigorous work of conceptual analysis, with nothing to replace them. I do not think that what I suspect to be a working redefinition of the word "philosophy is an example of "normal" lexical evolution, where, for example, the word "methodos" (meaning "crafty" in its original Greek) gradually evolved to first mean "way of inquiry or pursuit" to now be today's modern "method", the meaning of which is "systematic procedure"; rather, I see the particular working redefinition of "philosophy" as a type of "lexical hijacking" of an unconscious and potentially very dangerous sort (elsewhere in this thesis I have drawn attention to this phenomenon by invoking the term "conceptual slippage").

Conceptual analysis is not simple or easy to begin with; but I suspect that the above-mentioned redefinition, taking place while we are essentially "asleep at the conceptual switch", submerges or at least seriously obscures what a word like "philosophy" might have denoted, say, just 100 years ago. Rather than denoting a rational system of beliefs and rigor having to do with logic, epistemology, ethics, metaphysics and aesthetics, today's ongoing redefinition of the word has it increasingly denoting what one might best call an "attitude" towards what are commonly seen to be a set of "hot button" political action and decision items (e.g., pollution; 'greening" of technology; conflict; global warming; abortion; etc) often characterized as an "attitude"7.

7 "What is your attitude towards 'x™ is quite a different question than "What is your belief about 'x'". An attitude is commonly understood to be "an individual's degree of like or dislike for an item" while a belief is usually understood to be what "an individual holds [based on a] proposition or premise to be true". In this sense "attitude" can be interpreted more as "taste" for one thing or another, while "belief" can be interpreted to represent what one holds to be true and as such holds more weight than "taste". Therefore "belief" can be seen as being foundational about truth, more "anchored" and arguably not easily modified or affected by anything except evidence that would inarguably demonstrate that what was held to be true is no longer; "attitude" on the other hand can be seen as having little if anything to do with the truth of any proposition, and is more alterable, malleable, changeable, shallow, easily subject to modification following a passing trend, a temporary condition, or a new experience, and more subject to being affected by what happens to satisfy the needs of the moment One can thus have positive or negative attitudes towards something or someone as an object of like or dislike

85 To illustrate: here we might have a "sound bite" of a prominent politician being challenged by a legislative body with the question: "Well, sir, what is your philosophy about teaching a balanced curriculum with equal representation to creationism and evolution?" Or perhaps such a question could address balancing economic development with ecological diversity. Hypothetical response: "My philosophy is that we should have equal opportunity for all, in all things that concern us and our well-being, except when it just doesn't make sense to do so." I acknowledge that this is a contrived exchange, but it is meant to show how the word "philosophy" denotes a prescription of "what a person believes should occur or be the case" but this is intimately coupled with the "political correctness" and "political palatability" of the day. Thus: can a politician successfully defend his or her philosophy (if he or she actually knows what that might mean) and simultaneously communicate honesty, trustworthiness, reliability, good judgment, and clarity of thought? This is very hard to do. The word "philosophy" therefore migrates into the territory of being a "weasel word" that is itself not generally perceived to be trustworthy, and is increasingly interpreted to be a term denoting lack of clarity, perhaps including the intent to confuse, or reflecting surreptitious motives. The authentic meaning of the word "philosophy" thus becomes lost in a poorly elucidated, increasingly muddy and wretchedly convoluted syntactic sea. I therefore believe it is no mystery at all that the word "epistemology" is not in common currency, and that only professional philosophers, linguists, or a highly reflective subset of scientists might think of and use the word to reflect its authentic denotional meaning. The rigorous conceptual analytic work associated with the term "epistemology" is, at this time and in relative terms, too difficult for many if not most; it does not easily roll off the tongue; and, it is not a word that can be readily

(hand-made chess pieces, or the way the Prime Minister dresses in public, for example), but one can only hold beliefs about whether something is or is not plausibly true (that the current Prime Minister never wears a feathered boa, or is a good banjo player, for example). The assertion that you like Mozart or The Grateful Dead has to do with taste and presumably what music you generally find to be enjoyable, and as such cannot be based on what you believe to be true or false; the assertion that you believe exposure to classical or late 60s rock music cultivates creativity has to do with what you hold to be true about the relationship between the enhancement of creativity and the effect of listening to certain kinds of music, and ca not be based on whether or not you happen to like or dislike classical or late 60s rock music.

86 moved over into a simpler denotional realm to be assigned a less challenging or a more "plastic" set of meanings.

This is the foundation for my exploration of epistemic clarification. Although I think emerging new science like any other human enterprise by default must use common denotional terminology and deal with "normal" lexical evolution as well as the possibility of "lexical hijacking", I suspect that the underlying epistemic terrain of emerging new science (and of innovation and organizational policy) has much more to do with both the shaping of our scientific endeavours and successes, and therefore the unfolding of our future, than we might normally recognize — or care to recognize. Partly on account of the above-mentioned denotional dynamics, I suspect that the connections between the emergence of new science and its philosophical foundations and workings are not generally well or deeply known, or clearly shared or understood, by the major actors. This would be directly in keeping with Collingwood's picture of the increasing separation between science and philosophy. Therefore, words, terms, concepts, questions, problems and explicit speculative thought and conversations related to the epistemology of emerging new science seldom if ever appear in broad circulation; and, the epistemic referents for and therefore the meaning of terms like "philosophy" that are included in today's science and science policy communications are shifting to denote such things as actors' attitudes towards and arguments about such things as the above-mentioned higher-profile "hot button" issues, and the much less high profile aforementioned interdisciplinary aspects of new science and their technical and political constituents. This implies that, as a rule, the deeper epistemic frameworks that underpin the emergence of new science are not regularly or carefully examined. Although a relative exclusion of epistemology and a stronger emphasis on the technologies and politics of new science may be highly productive in the short term (measured perhaps in decades), this move, I think, may not helpful in the long run either for the epistemology of emerging new science, or the larger framework of the work of science in society generally. I am here questioning the longer-term implications of turning our attention away from the epistemology of new science,

87 and thus a clear understanding of innovation and organizational policy supporting such science.

In this sense, I think that the authentic, somewhat difficult and potentially very helpful epistemic clarification of emerging new science — which I would argue is the philosophical substance of the foundation of science — is today being trivialized to questions of what is thought to be the style of the foundation of science, primarily emphasizing the sensational aspects of technology and politics. To use the common vernacular, the sizzle is replacing or perhaps has already replaced the steak; or, at least, the meal that we thought was so promising is missing at least one very crucial component. This, I think, generally describes the default state of affairs with regard to the absence of the epistemology of science; and, I do not think that, in the larger and longer-term scheme of the evolution of science, innovation, or organizational policy, this state of affairs is helpful or particularly healthy.

In the next section of this thesis I explore how the drawing of inferences, a key component of epistemic clarification and thus philosophical deliberation, is related to the type of health addressed here. This is an essential next step in exploring the realm of philosophical denial.

88 Chapter 5 - Ouine and The Drawing of Inferences

Let us being the fifth chapter of this thesis with help from Alfred North Whitehead who stated that:

"... it is of the utmost importance to be vigilant in critically revising [our] modes of abstraction. It is here that philosophy finds its healthy niche as essential to the healthy progress of society ... [through] the critique of abstractions. A civilization [that] cannot burst through its current abstractions is doomed to sterility after a very limited burst of progress..." (1967)

Here we shall suspend consideration of what Whitehead might have meant by the term "modes", but still move forward with the remainder of his claim. It is not difficult to find what he has to say somewhat worrying, especially in light of the purpose of this thesis. That is, how do we critically revise our "modes of abstraction" so as to avoid sterility (and its presumed consequences of non-existence)?

Let us also remind ourselves here of Willard Van Orman Quine (1969), who pithily observed that "(c)reatures inveterately wrong in their inductions have a pathetic but praiseworthy tendency to die before reproducing their kind".

Whitehead and Quine together suggest that how we draw inductions — wrong or otherwise — may be connected to our ability to revise our abstractions. What are Whitehead and Quine saying? We now seriously consider and explore what they might mean. Here I will explore how a tendency to be inductively wrong, or at least inductively inadequate, might be connected a lack of critical thought and thus to denial of philosophy. In conducting this exploration, I will take defensible liberties with Quine's observation by generalizing, for example, from inductions that are wrong to inductions that never happen because they are denied, and what this might mean with regard to the tasks of epistemic clarification. In so doing I will attempt to not become mired in a swamp of impossible thought

89 To explore how Quine's claim is interesting, useful and illuminating in consideration of the above, let us begin by reflecting on the following: just what would his doomed creatures be like, what characteristics of their contexts would have brought them to the point that Quine contemplates, and what would spell their doom? What characteristics would they have — or, perhaps more importantly, not have? Pollack (1991) or Kauffman (2005) might suggest that their ability to move to new coordinates in their state space is limited — that is, within whatever parameters of behaviour, genetics, physical structure, and even cognition provide compass for what they do and what they are, they do not possess any meaningful, helpful or useful "pre-adaptive capacity".

At this point we have ventured into the first 350 words or so of this fifth chapter and already we must be cautious. "Pre-adaptive capacity" — what might that be? This is a dense, somewhat woolly term, laden with multiple shadowy concepts, potential significance, and, I think, containing dangerously conflated meanings. However, the general concept is interesting as it suggests system conditions that given their dynamics and characteristics provide a narrowed range of possible outcomes, and this might be interpreted as a species of determinism; and, the term has both functional significance and conceptual relevance to (and its origins in) evolutionary biology and in chemistry (Law et al, 2009; Corey, 1990). But, taken generally, the term suggests some of the necessary and sufficient conditions for a system to learn and adapt within, and to navigate through and achieve adaptive advantage, especially through multiple generations, in a larger context or environment that itself may be presenting challenges and change.

Let us reduce the degree of conflation and explicate the term at least in part by suggesting that Quine's "pitiful" creatures — agents in that changing environment — are lacking any strong capacity to learn from their experiences and thereby adapt to their evolving context They may have excellent memories of accumulated experience and superbly refined senses for perceiving what goes on around them that provide input for their infallible memories (or, alternatively, we

90 can hold the possibility that they may have neither); but, regardless, learning and adaptation are not central to their repertoire, if they can be considered to be in their repertoire at all, or if they can be considered to even posses a repertoire.

To tease apart what this means, we must explicate some important aspects of pre-adaptation's constituent parts, of which there are at least two that are arguably critical.

First, in order to have potential capacity for learning, it would be difficult to think of our Quineian creatures as being "of a piece", to be uniform throughout, something like a block of homogenous cheese or pure silver. Instead, they would have constituent differentiated parts, "building blocks" if you like, that when taken together comprise their "creature-ness" (let us be generous with Quine's terminology and here envision eyes, arms, and legs, for example; a nervous system to coordinate it all and perhaps specialized sectors of a brain specifically related to those parts; organs and their systems; and, for sake of argument, all the genetic bits that make put all those pieces together and ensure that they all work together). But most importantly, even with such a configuration, they would not have much if any ability to utilize those blocks to assemble some novel capacity capable of bestowing advantage from modification of the connections among those constituent blocks. Although they might accumulate a lifetime's worth of clear and very accurate memories — envisioned perhaps as watching a highly detailed video screen of life from beginning to end, but with no way of interacting with the "outside" where events actually do take place — they would have little or no capacity to build from or upon what is remembered (conversely, and quite obviously, if their memories were not quite so good, they would have little to remember, no matter what). They could utilize their "blocks" to do the things that would be determined by their "initial condition" configuration (that is, they could run an equivalent of an activity program — an algorithm — based on the initial configuration of their blocks, with some logic architecture). But they would make much better inductions (and perhaps, even more fundamentally, actually be capable of inductions) and thus have

91 a chance for enhanced (adaptive) survival, if they were blessed with building blocks and connections among them that could, when re-organized or re-aligned in some novel fashion, result in new configurations of the architecture that could successfully carry out a new activity program [that is, where first-order blocks could be reorganized to run a new program, or perhaps utilized to create second-order novel meta-blocks).

Secondly, in their short lives that would eventually lead to extinction of the line, Quine's creatures would not have any significant capacity for self-modification to carry out any novel autocatalytic re-assembly of those l^-order blocks — to re align, connect, disconnect, re-connect, and reconfigure, in order to learn from previous experience and evolve into something new. They would be forever frozen in their original configuration, no matter what that configuration started off to be. No matter what is experienced, although it might be remembered vividly on account of an excellent memory, no change to the original program takes place as a result Thus the activity program generated only from their initial configuration — their original program — would be the only activity program available. Nothing else would exist. There would be no alternative program. Without reconfiguration, no new program could be acquired, and therefore no new program could ever be run. Running the original program and the original program only, no matter what the input or the environment or pressures for modification, is simply not an adaptive process. Hence launching this section with Quine's comment.

The thought of Quine's creatures not having any ability to reconfigure is highly significant With neither new blocks nor new connections to affect them, extant blocks would be simply that — blocks and their connections existing, frozen, in a particular arrangement resulting from their original default assembly. However they are arranged they cannot be changed, and therefore the work that they accomplish by virtue of the activity program resulting from their initial arrangement is only of the nature that results from that arrangement The system that is that arrangement of blocks has a static, fixed number of connections; and, if work is

92 accomplished by virtue of those connections, the output must by definition also be limited only to that work. We can think of the activity program and therefore the action taken by the block assembly as an equivalency representation of the original block arrangement The unchanging hardware, and the software that runs upon it, end up being different expressions of one and the same unchanging state of affairs. The output is always the same.

We can explore these ideas further by thinking about a talus slope8 somewhere in your favorite mountainous or hilly terrain, for example. Few would think that such an arrangement of rocks, sand and gravel is alive. It is certainly not self-motivating, nor does it reproduce. But, do the materials in the talus slope undergo re-arrangements? Through empirical observation over time, we of course conclude that they do — and they do it regularly, as conditions change. Why do such re-arrangements take place? Given their initial conditions and dynamics of the system of rocks and gravel interacting with its environment — an environment with gravitational forces, friction, electrostatic charges, chemical activities, wind, rain, snow, frost, earthquakes, the disturbing forces of animals traversing, trodding upon, or landing on the talus slope face, an airborne seed taking root and pushing the sand and rocks apart, perhaps the occasional rare meteorite or even golf balls arriving on errant trajectories having been dispatched from the local golf course, etc. — the component parts of the talus slope undergo various re-arrangements at many scales when impacted by these things. Do we notice anything of interest about their re arrangements? Yes — the angle and gross appearance of the slope appears more or less constant and yet, as it is goes through continuous multi-scalar perturbations, it moves in small, medium, and even large avalanches. Given their initial conditions and their re-arrangements, do the slope components accomplish anything by first being in their initial state and then arriving in a new arrangement by virtue of some external force? We could re-ask the question: does the talus slope compute? Here

8 A talus slope is commonly understood to be a pile of broken rock fragments and other debris that has accumulated at the base of a steep cliff or promontory. Talus slopes are extremely common in mountainous terrain, for example.

93 we have Per Bak's sandpile avalanches (1996) — a relatively small number of which are large, a relatively large number of which are small. A logarithmic plot of avalanche size versus number reveals a power law of perturbations in the talus slope. If the talus slope can be thought to compute, the result of the ongoing computation is represented by its dynamics and overall angle of repose.

But following thermodynamic laws to move through power law expressions of achieving lower potential energy levels and higher degrees of entropy — doing work, in other words — does not mean the achievement of anything at all except system dynamics verification if there is some external agent aiming to verify this type of thing, or, if you like, undertake to reveal those laws. The question of whether the tree makes a sound in the forest if there is nobody there to hear it is related to this. Of course the physicality of the system interacting with its environment that includes a compressible medium distributes and dissipates energy throughout that medium released from the physical re-arrangement of the system's constituent parts. The supernova does indeed generate sound waves in its surrounding compressible medium, and through our observations of that medium we can learn of them and their evolution, although no human ear will ever hear them. The work accomplished — the increase of entropy — is the distribution and diffusion of energy released through the rearrangement of cellulose molecules in and around the tree, or the molecules and atoms and their constituent parts and their energies in and around the supernova. A human who makes observations of the energy distributions and dissipation over time might begin to infer from the data collected about said observed systems that certain physical laws may plausibly underpin the observed actions and behaviours of the systems' constituent elements, and might even posit that some basic physical laws might hold true in the case of both relatively proximate Earth-based systems as well as exceptionally distant interstellar systems, and any others that we care to examine — that these might therefore be universal physical laws amenable to discovery. From this process, tentative theories about the relationships among components of a wide variety complex systems such as forests and supernova could be developed, leading to new

94 hypotheses and the collection and analysis of new observations perhaps of novel systems, or perhaps new analyses of old archived data, to test those hypotheses.

From this we could conceivably generalize and discover that many if not all "sandpile" systems exhibit such power law relationships (indeed, this appears to be a primary characteristic of such self-organized complex systems poised in a critical state; see Jen [2005]). The basic concept is that whatever is being observed, there are many small examples of those things and increasingly smaller numbers of larger examples.9 This could include such things as sunspots, predator-prey relations, traffic jams, red blood cell flow, links among nodes in cell phone networks, star quakes, schools offish in particular and the behaviours of living swarms in general, Internet connections, immune system responses, and cardiac ariythmias — to name just a few. So the work of "sandpile" systems is to run what I have here described as their "block" programs in whatever hierarchies and distributions determine their configurations. All the constraints and variables that constitute the sandpile system and its interactions with the sandpile's environments is whatever it takes to increase overall system entropy by running the program — even if there are components of that system that appear by virtue of their membership in that system to decrease local entropy by learning how to position themselves advantageously in their state space, acquire energy from that space, and perhaps even begin to have effects on that space.

The overarching thought of decreasing local entropy allows us to necessarily jump to a divergent track of thinking about complex systems that do indeed successfully learn and are adaptive, that are thus not at all Quinean in nature. This notion rubs up against the previously mentioned "wooly" notion of pre-adaptive

9 Graphing the relationship yields a power law with a slope of approximately 1.5 (Kauffman, 2006). An interesting observation is that many widely-varying sets of "sandpile systems" that present with large numbers of small events and small numbers of big events appear to have a power law relationship yielding a slope of approximately 1.5. Why would this be? Is there a deep physical law of some sort that underpins this apparent characteristic of complex systems? At this time, the reason or reasons for this behaviour across widely varying sets of such systems remains unknown.

95 capacity (see Bock 1959), which I dispense with here10. The inferences they draw are not generally wrong; indeed, they are more often than not correct — and it appears they can make extensive use of those inferences. What is going on here if we think about they type of systems — perhaps we can think of them as "post- Quinean" — that can learn effectively from the inferences they draw, and in apparently special cases, with what appears to be conscious intent, modify themselves and enhance their own capacities to learn and adapt?

1st and 2nd order structure and function leads inevitably to the second type of necessary and sufficient conditions — that is, the creatures in whom we are interested require extant system dynamics capable of carrying out assembly of those original blocks through use of those original tools into novel functional configurations that did not exist prior to assembly — configurations that are capable of accomplishing things that the previous configurations could not, things that provide adaptive advantage.

This suggests a systems dynamics program capable of organizing for some finite time the operational dynamics of 1st and 2nd order blocks and tools to accomplish 1st and 2nd order work, some of which is what might be best thought of as iterative feedback loops of self-modification and assembly, disassembly, and re assembly. Work requires energy and therefore it would seem logical that another component of the operational dynamics would have to do with perhaps seeking but definitely utilizing energy available through traversing some type of

10 My sense of the meaning of this term can be explained as follows: let us denote as "A" a constellation of circumstances (e.g., characteristics) that happens to exist (having already been selected / self-selected to reliably be identified as that constellation), and let us simultaneously denote as "B" a constellation of circumstances (characteristics) that happens to exist (having already been selected / self-selected to reliably be identified as that constellation). Thus "A" and "B" reliably exist "A" runs an operational program that we denote as "pA"; "B" runs the operational program that we denote as "pB". Let us describe the output of "pA" as 90%"d" and 10% unknown but not "d", while the output of "pB" is 25% "d", 75% of which is unknown but not "d". Let us now ask two questions: [i] which constellation of self-selected circumstances has the strongest preadaptive capacity for "

96 transformational energy gradient in the system's environment Perhaps energy for work could be acquired by employing the tendency of certain chemicals to store and then release energy under certain conditions. This then suggests that the system we are beginning to envision would be neither a fully open nor a fully closed system, but would perhaps be variably partitioned to permit efficient rather than random storage and transformation of energy — perhaps with the equivalent of semi permeable and filter-like separators — into specialized but coordinated units carrying out different types of work and thus making energy available for transformation and exchange. This begins to sound like a plausible way of viewing biological cell specialization and the establishment of specialized systems of such cells. This also raises the question of how programming for specialization, diversification and coordination could come about, be utilized, and perhaps be stored for re-use based on modification. This begins to sound like storing, replicating and applying information — instructions for such systematization and diversification, and then modifying those instructions given changing circumstances.

Only with these conditions met could Quine's creatures begin the process of self-modification and maintain successful reproductive and learning capacities in the face of opportunity, challenge or threat They would no longer be pitiful. They would no longer draw more wrong inferences than ones that are correct. They would become adaptive, intentional, learning agents.

From these points, and keeping any hint of mal- or non-adaptive (pitiful) Quinean creature-ness at bay, I believe it is essential that for the purposes of this thesis we raise into consciousness a terrain of inter-related practical and philosophical issues that have to do with how we shape our future with more intentionality than passivity — but, in the realm of how to usefully employ philosophy in the context of our real and operational world, this is a tough sell. We are neither used to or particularly comfortable with doing this sort of thing, and it may very well be that we actually do not know what this means — and, we tend to

97 play it safe about what we think is important for our future. We like to hedge our bets, and we also tend to do marvelous jobs of engineering and hypothesizing in delimited ways about what we think, perceive, and believe to be the case.

So, we now turn to a deep challenge: how do we deal with a complex constellation of variables coupled with pushing and perhaps making more flexible the boundaries between what appears to be "inside" (that is, the way we think about and perceive the word, viz, epistemic reasoning) with what we think is without (that is, the constraints and variables that appear to make up our living environments and our world), and especially, what we inevitably learn makes up that external world? That is, how can we do our best to become post-Quinean, draw increasingly good inferences, and by extension optimize our adaptability and learning potentials?

The assumption is made here that an external world does indeed exist, independent of and beyond our senses and our subjective perceptions and interpretations. The question of whether or not this assumption is defensible will not be addressed in this thesis. Thus we assume that we are used to dealing with what we think we see as the outside world and what we have concluded we already know about it. We run our "block programs" and, on a broken front, employ learning to modify those programs for adaptive purposes. Things that are "new" are usually understood to exist more or less just along the relatively safe outside edges of this world where new things live and are created in "the adjacent possible" (Johnson, 2010) where, presumably, we aim to possess optimal "pre-adaptive capacity" (but per footnote 9 we shall not again use that term here) to explore what is possible. We therefore tend to explore where we believe things are not too different from what we already know and what we believe to be the case, that is, not too far from shore; pushing the envelope on how we think about things and what we believe, and heading out into deeper waters doesn't happen all that often — unless we are thrown dramatically into a world we didn't expect, or we intentionally take an exponential leap to head off towards the horizon, leaving safe harbor behind to explore the unknown. The further we are from what we know — the further we

98 push into the nether regions of the Johari window — the stronger we tend to assume the risk to be, and it seems this goes hand in hand with what we think of as challenge and perhaps potential reward if we successfully overcome or reformulate that risk. And often it is here that we are faced with challenges we could not anticipate or dream of anticipating; and sometimes, it is life or death that can result in either outcome.

So the question becomes: what is it that goes on when we are surprised, shocked and forced to learn something about that which happens to us, when we encounter something new that is unavoidable — or, if we intentionally push beyond the horizons, and we encounter things well beyond our "comfort zone", if we find ourselves in our complex adaptive system pushed to the threshold of creating — or even becoming — a cascade of Bak's power law avalanches?

We have some choices then. First, we can deny what we encounter. We can refuse to acknowledge our experience and filter out clues that might lead us to fuller awareness and even a chance at survival. In so doing it may be the case that we may not be tuned into reality, but we remain secure in our view that the world is not really that different "out here, right now" than it was "back there, back then": we arrange our thinking to see things the way we have always thought them to be. We can run the block program and never engage in modification based on input of experience. Second, we can take direction from the Zen master who advised, "What we are doing is very urgent, so we must slow down." This is not gratuitous advice. If we avoid leaping to conclusions with what we encounter beyond our comfortable edge, and if at the same time we remain open to reflection (recursive thinking) about what we experience, we give ourselves time — at least, some of the time that might be available to us — to assess, to cope, to learn, and perhaps even be able to survive and prosper. The panic guidelines of "ready, fire, aim" guarantee only that shots are fired, not that there is much chance of hitting any desirable target Unintended outcomes can proliferate and be very serious indeed when we leap before we look. Like Plato's archers launching their arrows into the dark, this

99 sounds like the drawing of poor inferences of a decidedly Quinean creature — one that is not long for this world.

As adaptive and learning creatures, not Quinean (so we hope), it is the case that our views of the world change — necessarily so given that the world is far from constant When those worldviews change and we engage in reflective thinking, we are engaged in something called "epistemic evaluation".

But for most this sounds suspiciously like a foreign language, and for many, it surely is. What I mean by this is the following: the word "epistemology" might have been a term commonly used in Left Bank coffee shops in the late 19th and the early 20th C, but in the current era, you must be committed to looking for a very long time to find it on the front page or on the cable television news. The term is not common currency and what it means is not in regular explicit circulation. You can't find a road map with directions to new epistemologies, or suggestions about how to recognize them when you encounter, shape, learn about, and embrace them — when we are faced with these challenges, we have to find our way the best way we can with whatever tools we have at the time. Ask somebody on the street what he or she thinks about changing epistemologies, and they'll most likely point to where diapers are available in your local pharmacy. Not many people think deeply in an explicit and reflective sense about epistemologies over their morning cereal, while having a shower, or while they settle down to read after supper (although it may very well be that those same people are indeed thinking epistemically during those activities, perhaps without realizing it). Very few think rigorously, or at all, about epistemologies or what epistemologies are while they do their work. Of course some philosophers whose job it is to think explicitly about epistemologies do precisely this, and in fact they might even talk and write about them. But epistemologies are not something that the vast majority of people ever find themselves consciously examining, reflecting upon, or even knowing about Like a pair of glasses that sit in a jacket pocket hanging in the wardrobe, long forgotten, we are mostly unaware of what we carry around as our epistemological frameworks or where we have filed

100 them away. We take them for granted even if we are distantly aware of them, and don't think too much about what they are, what they do, how we use them, and how we might improve their use.

To this point in this chapter we have now encountered the point of view that systems with which we are familiar that are neither complex nor adaptive may through their activity follow physical laws that reduce entropy, as it seems all such systems do. However, we have come upon the notion that learning and adaptation that permit autonomous changes in activity appears possible only in what are denoted as complex adaptive systems. Such systems are not Quinean (with reference to Quine's comment utilized in the opening of this section) — they do not have a pitiful tendency to expire, but an admirable capacity to learn, adapt reproduce, proliferate, and persevere. One might suggest that they have adaptive intelligence, if we can define intelligence that way.

We have also introduced some thoughts about epistemic clarification, and thereby suggest that we might wish to explore epistemic systems — that is, systems of knowledge and belief. Starting with Quine's comment, we have come to a point where we can begin to think about generic complex adaptive systems that can learn and adapt and have a reasonable chance of survival, versus those that do not.

Let us now redirect our thinking to consider what this means in terms of epistemic clarification, the work of philosophy, and the focus of this thesis — the denial of philosophy.

The fundamental claim of this thesis is that, in the current era, potential benefits of broadly-applied authentic philosophical work are generally unaddressed and unknown — not because philosophical work does not generate benefits or value, or that any such work that has been carried out in the past has not been beneficial — but because today, philosophical work is not commonly understood, consciously recognized, seen as normative, rigorously carried out, or broadly

101 applied in what we perceive and think to be the world of which we are a part Epistemic philosophical work has therefore been become neglected, generally forgotten, and is today broadly ignored, unexplored and unknown. I am positing a generalized phenomenon: that is, I suspect that to make the assumption that philosophical work is the business of philosophers and no-one else is a large part of my concern. I am suggesting here that philosophical work is the work of all people.

Although I do entertain the idea that the overall absence and systematic denial of authentic philosophical work today may be a result of outright passive benign neglect, I also see a more serious problem: the strong possibility of active delusional effort the object of which is not only denial but destruction and elimination of philosophy and its work. I will return to the notion of outright epistemic war with regard to the work of philosophy nearer to the end of this thesis.

So, in general terms, when from time to time philosophical challenges are encountered or stumbled upon and perhaps even partially recognized as such, they may receive a nod of acknowledgement but appear generally unanswered and are placed on the sidelines. Whether this placement is a consequence of neglect or design, or both, remains to be discussed. Regardless of the motive for generic sideline placement of philosophical challenges, except in highly specialized environments such as departments of philosophy at universities where philosophical questions are the focus of thinking and work carried out, they are routinely denied. So, an initial question addressed here is: if the denial of philosophy in a broad sense is real, why would this be the case?

This thesis goes further than claiming that philosophy is broadly denied. It also claims that regardless of whether such denial is a result of neglect or design, the situation of broad denial of philosophy is a serious problem in consideration of how we frame our beliefs and think about and live in the world, especially with reference to things that we routinely think of as being very important for our achievements and successes, such as innovation, sound organizational policy, and the productive

102 advance of science. The assumption being made here is that we can only fully understand and optimize what we take to be innovation, sound organizational policy and the productive advance of science if we know how these things are founded on, shaped by, and have an iterative formative relationship with our beliefs and how we aim to live in the world.

Leaving religion and faith out of our consideration for the moment, these three fields appear ubiquitous in how humans organize themselves, generate and advance knowledge, and collectively carry out our greatly varied practice — few would argue that these fields are not central and foundational to how we live our lives today. In broad terms, these three fields are used in this thesis as specific examples of apparently very significant human endeavour. This is here taken to mean that we recognize the value and seem to care very much about these three features of what we do, that we attempt and do many things as we live out our lives to try to make them work well if not better than they have in the past, and we do this so they will be increasingly productive in our service — all founded on what we consistently take and believe to be true and reliable. And that we do this in service not only of our present-day interests, but in the interests of those who will follow. We know we leave a legacy. We want that legacy to be positive, helpful, enjoyable, and prosperous. Apparently, we desire the good life for all.

In the realms of innovation, organizational policy and the advance and development of science — which I take here to be core aspects of rational operationalization and achievement of human goals and desires for enhancing systematic knowledge, productivity, and well-being — we are exploring what appear to be strong examples of evidence for the common denial of philosophy, in particular in these three realms. We are therefore at this point in this thesis illuminating a terrain of questions and challenges generated by said denial, its contexts, and its constituent parts. We are also beginning to contemplate what potential benefits might emerge from seriously engaging in philosophical exploration and thus what might be done to pursue enhanced philosophical work

103 aimed at perhaps overcoming, or at least reducing, said denial. We are moving towards suggesting that we can enhance our ways of thinking about and overcoming the apparent denial of philosophy and thus how we carry out our decisions and actions, especially in the three aforementioned fields.

We have suggested that evidence for the broad denial of philosophy is extremely common; that such denial is widespread; and, that the converse — broad ongoing considerations of and thoughtful dialogues about philosophical questions, philosophical issues, and philosophical work — is not.

This set of circumstances is now raising what 1 argue are important questions about why this denial seems apparent and why it might exist. Questions such as "Are we now living in a philosophical vacuum?" and "If we are living in a philosophical vacuum, what shall we do about it?" are key to where we continue to take our exploration. Addressing such questions opens avenues having to do with reflection upon and systematic examination of how we establish beliefs and what things we believe, what we hold to be true, how we justify these things, what we consistently think of as real — and thus, by extension, how we choose to live, act, prosper in and think about our lives in every respect.

If what I am proposing in this thesis is true — that the very concepts and presuppositions of philosophy as we have commonly come to think about them are broadly denied, such that collectively we might even think that philosophy and its applications have little if any use, or if we feel inclined to agree with the most extreme view along the lines of Hawking and Mlodinow's (2010) argument that philosophy is dead, that philosophy does not exist — this could mean a number of things that can illuminate this exploration. For example: could this mean that most philosophical questions which we appear capable of addressing, or that have been developed, explored and addressed in the past, have now been answered — that, essentially, the work of philosophy is done? Could this mean that there is no longer any need for pursuing, engaging in or even thinking about philosophical work? If so,

104 have we come to a state where we have forgotten how to engage in philosophical work simply because we think such work is no longer necessary — if it ever really was? Or, are we even aware that we might be in such a state?

Could it now be the case, if we ever do encounter a question that we suspect might be philosophical in nature, that all we have to do is ask a computer to look up the answer in some philosophical reference that we have been assured is as complete and as trustworthy as possible, as if it were a phone number or an e-mail address, something already there and in its proper and available place as a result of someone else's or some other thing's work, to which we can readily refer, retrieve and apply? That, if we ever do find ourselves puzzling over a question that we think might be philosophical in nature, do we assume the answer has already been reliably placed by someone or something else, exactly where it where it ought to be, so that it can serve as the answer, filed in and available through some compendium of accumulated knowledge where it now resides somewhere in an amorphous computerized cloud — and that, when prompted, some Google-like oracle will silently and invisibly navigate that cloud on our behalf and promptly provide the answer for us? Can questions that are philosophical in nature be "answered" in this way? If we do not give what we suspect might be a philosophical question or challenge any thought or consideration, but instead turn to some "built" knowledge compendium in order to find what is purported by that compendium system to be the answer, have we engaged in philosophical work? Or have we merely looked something up in the compendium? Can what is provided for us by that compendium system actually be considered to be the answer if we, ourselves, have in fact not given much if any thought to the question but have perhaps restricted our "work" to data mining and finding correlations among things in those data — to find what we think is the answer?

Let us take a slightly different approach to these questions. Could it actually be that philosophical pursuits have, over time, been reliably demonstrated to be fruitless or considered, in some way, to be "of low yield", and have thus been

105 abandoned for other courses of thinking, shaping of world views and taking action that are thought to be more productive and have more relative value given our circumstances, and provide the optimal level of what we apparently both want and need to do to prosper — a higher "return on investment"? If this might be so, why would the work of philosophy, and perhaps even philosophy itself as a field of knowledge and inquiry, have come to this state — to be considered to not be of much value? Why is serious consideration and pursuit of philosophy either not much in evidence today, or thought to be an exceptionally difficult task that leads nowhere? Why would some of the world's leading scientists, for example, have argued, stood on reputation and worked hard to claim that philosophy is a "pleasant gloss" on the "real" work of science?

From the perspective then of collective ways of living in the world, what broad effects on systems of belief do such claims have on the capacities of others who may not toil scientifically to carry out the work of philosophy in their own areas or fields of specialization? Why does it appear to be the case that a great many others disregard serious philosophical considerations almost entirely, as if they simply do not exist? Against the backdrop of questions having to do with "the real work of science" or the "real work of engineering", for example, where, then, is the "real work of philosophy"? And where does all of this today leave things philosophical in the human scheme of existence? Does philosophy have any relevance to today's "real work of life"? Can anyone venture a defensible claim that we know enough about life and how to live it that we actually understand what "the real work of life" might be, especially if (by virtue of our unprecedented knowledge compendia, data bases, and methods of searching them) we are losing or have lost our capacities to engage in "the real work of philosophy"?

We can entertain some thoughts about what some plausible answers to these questions could be. For example, in the current era we appear fixated on things like economic benefit, the achievement of innovation (and more and more innovation), and especially what we might think of as "measurable" achievements and increased

106 relative productivity and wealth in such realms. Why does it appear that we pursue these things to the virtual exclusion of things philosophical? Given how focused, dedicated, expert and busy we all seem to be, do we simply lack sufficient time, energy and concentration to carry out philosophical work — that is, is it a practical question of what we have available to us in terms of time and energy? Or, has the work of philosophical pursuit outlived its usefulness, only to be replaced by sailing the vast seas of data and information that continue to grow around us? Is the work of philosophy thought to be a waste of what we today tend to think of as our most precious commodities — time, attention and energy (and, parenthetically, why would we tend to value commodities more than other things)? Or, could it be that this kind of work is just too difficult for most people — that exploring philosophy, and reaching understanding of things philosophical, is just too hard? That, when push comes to shove, we just aren't very good at philosophical work, and tend to avoid it? Taken to a somewhat more extreme view, could it be that we have created a human environment where all of these things come into play such that the question of philosophical work and its potential benefits simply does not exist — that philosophy and philosophical work are now in the realm of the absolutely unimportant, totally irrelevant, the forgotten, and therefore unknown and the unknowable? That, if the idea of achieving wisdom remains anywhere in how we understand the benefits of engaging in philosophical work, such an idea has been dispensed with as irrelevant to and eminently forgettable in the single-minded commoditization of life where we can look anything up and feel sure we have the answer? Are we now well on in the process of denying wisdom?

And if this is possible, and if we dare go even further — are we today "normalizing" the denial and the final extinguishing of philosophy, the final erasure of its denotation, so that it is will no longer be considered in terms of any questions at all — where the denial of philosophy is itself denied, and then recursively denied so successfully ad infinitum that it has no existence whatsoever? Have we gone such a long distance down such a path of self-reinforcing elimination of concept and thought that, if we do happen to encounter or think about something that might be

107 philosophical in nature, we now happily define it as completely unimportant and unessential, and then dismiss and rapidly forget it? So that we think of such things when they do emerge as entirely nonsensical? Or, if the term "philosophy" remains in the human record, it ends up denoting something along the lines of "the phlogiston of human thought", or perhaps becomes a historical artifact denoting what humans did to fumble through the day in more primitive times? Are we moving philosophy into a state of a perfect non-entity so that there is no other view available to us — and there is no turning back?

To this point we have begun to develop a scope of thinking about what appears to be a puzzling absence of philosophy. It provides lines of reasoning about these and other questions, attempts to illuminate the terrain of plausible philosophical denial, and will lead to a conclusion that offers what will be argued is a critical choice — if we agree that it is not too late.

In the next chapter of this thesis I will focus on three examples of unprecedented demands on human thinking and ways of viewing highly complex and challenging science, and, facing such demands, the methods by which we attempt to achieve answers to extremely difficult scientific and commensurate engineering challenges. From this I will attempt to find the place of philosophy in undertaking such pursuits. For reasons that will become obvious, please note that I will leave commentary about the fourth example (faith and religion] for the second- last chapter of this thesis.

108 Chapter 6 - The Absence of Philosophy

To continue our exploration of where we might find another example of evidence for a contemporary approach to a set of leading-edge tasks that could have the potential of reflecting the relative significance of philosophical work — that is, where we could logically expect to find thoughtful and reflective work embracing and addressing the rigor of understanding the challenges at hand, linked to questions about the meaning of both the work itself, all of this coupled recursively with the work that is necessary to determine the meaningfulness of the work itself — let us examine the contemporary emergence of leading-edge new science in the field of astrophysics. In their article entitled "The Exploration of the unknown", Wilkinson, Kellerman, Elkers, Cordes and Lazio (2004) address the creation and use of conditions for and routes to scientific discovery in the realm of the leading edge, world-class, emerging science — in their particular case, with the Square Kilometer Array (SKA)11.

I commence this chapter by offering some thoughts about Wilkinson et al's analysis because, following my extensive experience and involvement with the Institute for Biocomplexity and Informatics, the Square Kilometer Array project now comprises a very large part of my current work where I am collaboratively responsible for resourcing, aligning, and helping to shape strategic direction for the project, particularly with regard to industry involvement. I am here offering a second experience-based set of observations about the absence of philosophy in a very large-scale, long-term, complex human scientific endeavour.

11 Please note that the three-letter acronym for the "Square Kilometer Array" is "SKA". The correct pronunciation of this acronym is the clear articulation of each letter in seriatum "ess-kay-eh", not a condensed "skah", or "skaw", the latter of which refer, for example, to a Jamaican music genre that originated in the late 1950s, or the Shotokan Karate Association in Calgary. Both of these are undoubtedly admirable and have significance within their own realms, but they have no connections with or any relevance whatsoever to the leading edge of radio astronomy. I suggest that any collapsed pronunciation of "SKA", however "natural" it might seem, in fact creates an error of denotation and therefore an increased risk of subtle (or perhaps not so subtle) conceptual slippage in relation to the meaning of "SKA".

109 The Square Kilometer Array is now in introductory stages of development, and the focus of both Wilkinson etal's article and the analysis they provide about that project creates for us a very useful vantage point from which to examine and reflect upon the core challenges that both face and, I argue, fundamentally motivate all modern scientists. Their thoughts shed light on how scientists hold beliefs about the practice of science, and what they hope to achieve by exploring unknown terrain through that practice — by engaging in the process of scientific discovery. It is this vantage point, generalized through other examples and the incorporation of perspectives having to do with beliefs and presuppositions that, through this thesis, will allow us to explore what appears to occur with what I am suggesting to be the very curious contemporary phenomenon of the denial of philosophy.

I suspect these challenges face those who support, wish to encourage and aim to develop a reliable framework for the generation of broad benefit from the work of scientists in the realms of scientific theory and practice, as well as in the realms of what are hoped to be beneficial economic or societal outcomes.

I also offer these thoughts because I think that the vantage point of the Square Kilometer Array as a real project in the world today that we can readily categorize as being "leading edge science" can allow us to gain a useful perspective into the philosophical foundation of scientific advance — a perspective which I argue in this thesis is essential to the development of optimal scientific achievement and all that flows from it, in particular if we incorporate contemplation of the aforementioned phenomenon of philosophical denial.

The first perspective on these core challenges has to do with innovation based on exploration and discovery — and then especially, with the organizational policy processes we develop and put in place to ostensibly encourage, support and enhance innovation outcomes.

110 The second and more fundamental perspective on these core challenges has to do with the epistemology of innovation and its relationship with the policy process, explored in more detail later in this thesis.

The claim underpinning these two perspectives is that without a solid understanding of the epistemology of innovation and emerging science when viewed against the backdrop of organizational policy, it is not possible to create the best conditions for optimal scientific exploration and discovery.

Taking this claim into account, let us examine the case example of the Square Kilometer Array introduced above. A brief summary of project follows. This summary will provide a sense of the level of significance and importance of this project in terms of science, engineering, data and information, and human organization — useful to know about, I suggest, so that the questions of denial of philosophy can be better illuminated.

6.1 A 2nd Example of Absence of Philosophy in Science

The Square Kilometer Array will be the largest and most powerful radio- telescope humankind has ever conceptualized and thought about in scientific and practical terms, and then designed, built, and then put into service as an instrument of scientific exploration (SKA 2009). Having been contemplated and planned for more than a decade at this writing and already taking shape in formative developmental "precursor" stages, the telescope will, when fully operational, be the biggest, most complex, most sensitive and, in a quite literal sense, the most far- reaching investigative instrument ever made. Its full operational mode antenna area totaling 1 square kilometer (hence the project name) will be constructed with three different types of antennae tuned to overlapping wavelengths of investigative interest. With a concentrated antenna core of one type, a surrounding halo of a second antenna type, and then up to five spiral baselines of many thousands of interconnected, networked receivers stretching beyond 3000 kilometers, the Square

111 Kilometer Array offers unprecedented engineering and computational design and construction challenges. Indeed, this project demands that these challenges are not only addressed but successfully answered.

The Square Kilometer Array low-noise amplifiers — extremely important components of the signal chain in the instrument and physically located on each one of the thousands of antennae — are now being developed and perfected as the world's best at the University of Calgary (Haslett and Belostotski 2006; 2010). They will have unprecedented sensitivity and generate through the signal chain what is anticipated to be between 700 terabytes (Tb) and 1 petabyte (Pb) of raw data per second, or approximately 8.6 x 10A3 Pb on an average operational day of data acquisition (Haslett, 2009). This is a very large amount of data — the rough equivalent of 4.9 x 10 A9 — 4.9 billion — full-length HDTV movies worth of data every day, or 57,000 such movies per second. To put that into human terms, if a person was to plan to watch one day's worth of data gathered by the Square Kilometer Array translated into the data capacity of HDTV movies, but then spread only that one day's data out over an average human lifetime (which we will arbitrarily state here is 78 years), he or she would be required to watch approximately 1000 HDTV movies per minute, 24 hours a day, non-stop, from the moment of birth to the moment of death. Remember, that's for just one day's worth of raw data from the Square Kilometer Array — an instrument that will be in full operational mode for a minimum of 50 years, or, 18,262days.

The data challenges here are enormous and entirely unprecedented. In terms of the astrophysical science that will be explored and then revealed through analysis of these data, all that is collected by this project must be triaged, parsed, streamed, processed, filtered, distributed, transmitted, stored, and made available for imaging, analysis and repeated re-analysis. Available technologies and the logic of inquiry tell us that this will take place through a vast global high-speed data network of waypoints and science centres specializing in a wide variety of advanced computerized analytics. Here we can recall the words of Duncan Hall, chief

112 information technology architect for the Square Kilometer Array, who made the public observation that "the SKA is in the computer" (2009), and Bruce Elmegreen of IBM responsible for that firm's collaboration efforts with the Square Kilometer Array who said, "what the SKA will almost certainly be can be envisioned as what we understand today as (what will emerge to be) the world's most powerful supercomputer — but amplified by many of orders of magnitude — with an antenna on the top" (2010).

It is useful to recall that given what is reasonably expected over the next few decades in terms of antenna, receiver, computational and engineering discoveries, designs, upgrades, and developments, the size and complexity of data volumes and collection rates will only increase over the life of the project to be larger and more complex than what has been briefly described above. Graduated Square Kilometer Array startup from approximately 2016 to 2022, taking place at the front end of the project before any further notable developments, will generate unprecedented rates, flows and volumes of data — far larger that what is projected in any other field of investigation (Syed etal 2010).

Through its expected 50+ year operational scientific lifetime to the year 2070 and beyond, the projected data volume, growth in that volume, and vastly increasing complexity of collected data will be larger and generate more challenges than any other that humankind has never seen or experienced (Elmegreen 2010; mediawiki 2010).

Although the Large Hadron Collider (LHC) has been built (and continues to be repaired at the time of this writing following a startup malfunction in September of 2008)12 and will itself generate huge volumes of data through its lifetime of

12 In 2011 this project has once more became fractionally operational and data are being generated and collected, but the power and therefore data complexity of the project are not anticipated to reach an operational maximum until 2012 or most likely 2013. At that time, however, it will still have a triaged data output and handling challenge estimated to be only 1/16"• that of the SKA (which works out to approximately 24Pb per day for the Large Hadron Collider, versus the estimated 380Pb per day for the SKA).

113 investigations into the frontiers of particle physics, humankind has never built a science-based project as large or as complex as the Square Kilometer Array, and has never dealt with, thought about, or faced such massive data flow, data growth and data handling and processing complexities and challenges. This means that although it is in good contemporary company from the perspectives of leading-edge engineering and computational requirements, the unprecedented challenges of data collection, storage, filtering, imaging, analysis and re-use emerging from the Square Kilometer Array will remain in a class of their own for the foreseeable future. Additionally, it seems likely that the threshold for defining the term "unprecedented" will move ahead in concert with developments that will continue to define this project Although some components of the engineering, antenna, receiver, collator, data handling, transport and storage, imaging and computational challenges can presently be put into place with current capacities and technologies, there are no immediate, comprehensive, pre-packaged, off-the-shelf answers to these challenges. Along with what is already known and available, these things must be invented and developed as part and parcel of the overall project architecture over an extended period of many decades to meet the evolving future needs of this project.

Because of the sensitivity, scale and scope of the Square Kilometer Array, it will be able to look further back in space and time, and with higher degrees of comprehensiveness, detail, and with greater resolution, than any astronomical instrument previously built (Taylor 2009). It will generate data about the universe that, through its various necessary stages of reduction, analysis and synthesis into information, may help us answer some of our most difficult and challenging questions, such as: are we alone? what was the beginning of the universe? is there such a thing as dark matter? was Einstein right about gravity? (SKATelescope.org 2010).

At this point of the story it is clear that the Square Kilometer Array will definitely be an impressive technological, engineering and computational

114 achievement It will, indeed, be the largest and most powerful telescope of any kind ever built, ALMA (Atacama Large Millimetre Array) and the LSST (Large Scale Synoptic Telescope) notwithstanding {ALMA 2010; LSST 2010). All of the features of the Square Kilometer Array project have their own unique challenges and developmental requirements. As such, they provide powerful motivation for those involved to solve unprecedented problems to build the world's most sensitive and powerful telescope, and especially, to make it work successfully over at least half a Centuiy to accomplish and even invent its investigative challenges and tasks.

But, leading-edge science, computational challenges and other wondrous technologies aside, let us think for a moment about what we can call the "knowledge architecture" of the Square Kilometer Array. Here we will examine what we know and what we expect to know by virtue of such a unique instrument. Such a large, long-term, highly complex project is based on fundamental knowledge from many different fields. This knowledge has to do with current theory and practice in the interrelated realms of physics, astrophysics, astronomy, engineering, computational sciences, design, systems architectures, materials science, devices, and nanotechnology, among many others. In the case of the Square Kilometer Array, simultaneously pushing the envelope in so many fields in a "loosely coupled system" (Weick, 1976) of science and engineering enterprise to create the "next insanely great thing" (Wolf, 2007) presumes necessary and sufficient knowledge about the required "building blocks" — very far indeed from Quine's pitiful creatures (or so it seems) — to move the entire project forward.

Most importantly, though, it also presumes that, where such knowledge does not presently exist or is now only loosely organized in some formative fashion, necessary and sufficient knowledge about our best methods of inquiry and development must be employed to determine and create whatever is required by way of optimal project building blocks that are not yet fully understood, or do not even yet exist Inventiveness and our best thinking, and of course adequate financial and logistical resources, are very much required to bring this project to fruition.

115 Wilkinson, Kellerman, Elkers, Cordes and Lazio (2004) map out what may be some of the most significant and meaningful guideposts we could ever hope to have that allow us to thoughtfully grasp and take clear and positive investigative and constructive action regarding what we think of as innovation, discovery, and exploration in all the above-mentioned fields. In the context of the special edition of "New Astronomy Reviews" providing more than 40 articles detailing the different types of scientific investigation for which the Square Kilometer Array has been designed, Wilkinson et al clearly articulate the deepest questions in astrophysics, which questions can be thought of as examples of the points of initiation and the foundation of any leading edge science (in this particular case, astrophysics). Their approach maps out plausible ways of thinking about why humankind would want to push the boundaries on exploring the universe.

Wilkinson et al's carefully crafted approach to discovery does not employ what we might commonly denote by the use of the question "why?" As encouraging as their essay about discovery might be, they are dealing with gathering evidence with a new and highly sensitive instrument, gathering unprecedented rates, flows and volumes of data, reducing those data to information (evidence), and then building and testing hypotheses developed to explain that evidence with the goal in mind — common to all science — to add to our frameworks of theory that help explain the universe. What does this mean? Wilkinson etal's motivating questions might be usefully phrased as "Can we discover what actually takes place in 'x' that can confirm or disconfirm what we have developed thus far as hypotheses to plausibly explain what we think we have observed thus far, at or near 'x'?" Put more plainly in terms of the work of modern astrophysical discovery, "When we gather, store and examine these unprecedented volumes, rates and flows of data, can we also build and use novel tools of analysis to reduce those data and then figure out more accurately ... what is going on in 'x'?"; or, more grandly,"... what is going on [in all of'a-»x']?"; or, even better —"... could new physical laws explain what appears to be going on [in all of 'aAn->xAn']?" and if so,"... what would we need to derive

116 from data collected from our observations to help build theory to suggest what those laws might be?"

Therefore the core of what is thought to be the ultimately exciting part of discovery would be reflected in the question: "What the hell is that?" — meaning, of course, that whatever "that" is has never before been encountered, posited, thought about, or imagined: in the parlance of astronomers, it is a "transient" so unique and different that it is surely very, very interesting — something completely unprecedented and new — a genuine evidentiary surprise. Such discoveries are relatively rare, and depend on the sensitivity and comprehensiveness of instruments used to gather data. One might think of their frequency of occurrence as being roughly analogous to Bak's (1996) very large but extremely rare avalanches. But it is the case that Wilkinson et al (2004) make a powerful case for supporting the Square Kilometer Array project by virtue of the increasingly strong likelihood that, through the use of this new instrument with its unprecedented sensitivity and resolving power, massive data output, and novel analytics, that such discoveries will be more frequent, that newly discovered things in the universe that have been unknown or even unimagined will be detected by the new instrument and then understood by scientists who analyze collected data (at least somewhat, as that understanding grows); and that discovery of this nature may perhaps lead us, eventually, to consider deeply authentic "why" questions, or even develop new ones.

So, the challenges, unique technologies and resulting discoveries of the Square Kilometer Array may indeed eventually lead to foundational questions that are philosophical in nature. The question then becomes: in planning for and building the Square Kilometer Array, is philosophical preparatory work being done at any level to deal with where the Square Kilometer Array may take us (that is, do we have evidence for explicit reflective consideration of the philosophical questions that will emerge as a result of the profound scientific discoveries that the SKA aims to make)? In what they have written, this does not appear to be the case. Scientists and engineers love the work they carry out inventing new tools and building new

117 devices and instruments, and successfully making them work and work well. They love their equations, and scientists in particular love discovery and everything that makes discovery happen.

However — especially taking the comments of Weinberg, Feynman and Hawking into account — it is not at all clear that scientists similarly love the work of philosophy, or that they see the relevance of philosophy to their inarguably important work.

Wilkinson et al also paint a clear picture of an optimal approach to the "how" (the methods by which we need to think about, arrange and build the components of the Square Kilometer Array, and what tools we need to put in place in order to acquire data about the objects of our investigation), the "how to learn from our mistakes", meaning optimizing the skills of the reflective practitioner (see Schon 1967; 1983) who engages in conscious, extensive abductive reasoning as advanced and described by Peirce (1934) and "what to expect when we think we have it right" (meaning knowing how to know that the processes and steps that have been taken have a correct logical connection to the assumptions, methods, techniques, applications and results of inquiry, whether they are anticipated or not, and whether they are surprises or not — and, most importantly, whether all of these things do successfully produce the data that can be properly analyzed and consistently transformed into information that does indeed advance our understanding of the universe).

In the context of the Square Kilometer Array and from these above- mentioned perspectives, what Wilkinson etal have mapped out regarding an approach to exploration of the unknown is entirely non-trivial. However, it is very important to note that Wilkinson et al also make no comment about how they have derived and developed their approach to exploration in astrophysical science, aside from intimating that what they wish to do is more of the same, only better and more refined using an instrument of unprecedented power. They do not relate in detail,

118 for example, descriptions of exploration and discovery in other fields that might have led them to formulate and then offer their suggestions. They might have turned, for example, to Hadamard (1954), Weisberg (2006), Ghiselin (1952), or Sawyer (2006) where they might have found the words of other thinkers addressing creativity, discovery and innovation, not only in science but other fields of human endeavour that would resonate with their underpinning argument They do not appear to have done so. No matter — I here suggest that the "discovery map" they offer can be usefully generalized to all aspects of scientific inquiry, and, if I may be so bold, to human inquiry in general.

But by "generalizable" I do not here suggest that what Wilkinson et al map out is anything like a "pat answer" or a recipe that can be programmatically followed for automatic success in the realm of scientific (or other) exploration and discovery. Against the backdrop of leading-edge scientific exploration in the SKA project, they have opened the lid on exploring the unknown and engaging in what we might think of as "deep discovery" — the discovery of things that can have considerable significance in the scheme of things — meaning: how we might develop our best thinking about humanity's place in the universe, and what the universe is all about.

We are here thrust back to Hawking who, as we have already seen, has made the claim that philosophy is dead. And here we can ask: can this be so? I am here reminded far more of the sculptor who gradually coaxes a warm artistic work of great originality from a cold block of marble than the programmer or programming team that creates what all other programmers agree is a beautiful product, along the lines of a novel mathematical proof. What emerges from the efforts described by Wilkinson et al does not reveal or suggest algorithms that when followed guarantee discovery or exploratory safe passage to a product

Unlike the inventors and contemporary purveyors of the more formulaic pathways to innovation offered for example by Altschuller (2005) through TRIZ

119 (acronym for the Russian Teoriya Resheniya Izobretatelskikh Zadatch, a "problem- solving, analysis and forecasting tool derived from the study of patterns of invention in the global patent literature"), Wilkinson et al have, I think, claimed their vantage point some distance from the creation of any definitive, prescriptive algorithm. I am confident, however, that as today's leading astrophysicists, they would be the first to acknowledge that the vast components of exploratory engineering and novel science which underpin the Square Kilometer Array are built by, dependent on, and for the most part developed and expressed almost exclusively through the use of algorithmic tools.

In so doing, Wilkinson etal have revealed something very important about what we can describe as both the architecture and processes of discovery and innovation. This may very much be in keeping with the kinds of initial conditions upon which Gould (2004) comments with reference to Poincar6 — that is, encountering the generative circumstances leading to insight and eventual solution. Rather than advancing a program one would describe and employ as a recipe to achieve a desired end (or, said another way, providing reliable evidence of what works and how this takes place even if one never fully understands why it works), Wilkinson et al provide a perspective one would use to create the conditions, or the space within which rigorous exploratory work could be generated and carried out — one might call this a generative conceptual space — followed by, or perhaps incorporated with some prescriptive and more algorithmic techniques and products: building blocks, if you will.

What they address is not so much prescriptive as what we might think of as "formatively descriptive". It suggests an approach to the challenges inherent in what we might call the terrain of discovery. They have not revealed anything along the lines of a program or prescription of discovery and innovation that could, for example, be run on a computer to generate what is hoped for. Rather, they have provided highly significant illumination of what might be best thought of as the terrain of discovery and innovation, where such terrain has an overall architecture

120 that in the case of the Square Kilometer Array is comprised of more than three dozen components of what we might term "new science enterprise", or leading edge science; thus, they suggest an approach to investigating the unknown, using highly specialized tools and the capacities to develop even more of those tools that can help us optimize innovation outcomes from those individual components, whether these are or end up being algorithmic or otherwise.

The requirement we are therefore compelled to meet in attempting to grasp what Wilkinson et al have to offer as they take the scope and scale of the Square Kilometer Array into account is to reflect as wisely as possible on their observations and commentary, rather than seek uniquely programmatic answers to the question of how to develop innovations and explore the unknown. We must therefore recognize that the value of the highly detailed specifics of the investigative tasks of new science enterprise and exploration that will be carried through operationalization of the Square Kilometer Array is enhanced by virtue of what we can think of as the approach to exploration, not simply the seeking of "instant answers" or programmatic approaches to questions of how to innovate or how to explore.

Wilkinson etal are therefore successful by suggesting how to situate an effective innovation architecture in the context of leading-edge scientific discovery, of which the Square Kilometer Array is a prime example. They also give every indication that they might illuminate a pathway or approach to what I argue is the necessary deeper deliberative contemplation of the philosophical underpinnings of leading-edge science — although it is not clear that they actually do this. Let us reflect on what this might mean.

6.2 - Reflections Stemming from the Square Kilometer Array

To this point, the backdrop to the thesis has been revealed and the direction of exploration has been presented. It is no coincidence that the example of

121 Wilkinson et al has been used as a transition to the following section, for here we have some of the world's best explorers explicating how they are convinced exploration should be shaped and steered with a forward vision of tackling the largest and most challenging scientific exploration that humankind has ever been contemplated.

However, even if Wilkinson et al have done an exceptional job of pointing out how useful a particular approach to exploration at the leading edge science can be, and if we can be so bold in this thesis as to suggest that what they have pointed out may help in moving discovery forward, have they explicitly addressed anything to do with commensurate philosophical work? Do they provide clear evidence that philosophical work by way of epistemic clarification has been considered in their effort? The answer is no. As with the story about the Institute for Biocomplexity and Informatics related earlier in this thesis, they do not appear to explicitly identify any need for any philosophical considerations or philosophical work. Admittedly, it is not clear that perhaps they did think about this but decided to exclude it from their article, nor is it clear that they did not consider this at all. They do suggest that the work of the Square Kilometer Array may help humankind answer some of its most important questions some of which are existential in nature, but it seems that is as far as the evidence goes. And this should cause us to pause and ask why, and especially, why it is important to reflect on the significance of exploration in science as it relates to the philosophy of science.

That is: why does this matter? Why bother? Isn't the sheer breadth, depth, extent and nature of the challenge of the the Square Kilometer Array — especially in terms of its massive and unprecedented rates and flows of data, which we have never before encountered, and the truly astounding new science that will result — of such overwhelming scientific, technological, economic, engineering, and even organizational size and importance that any philosophical work related to the Square Kilometer Array couldn't even be considered? That is, such considerations simply couldn't be on the table? In this instance, isn't trying to think about

122 philosophical work analogous to the impossible challenge of paying meaningful attention to (much less actually viewing) the thousands of HTDV movies per second representing the projected data flow of the Square Kilometer Array? How could anyone ever hope to do this? Can the work of philosophy possibly have a place on the terrain of such massive, global, emerging science? Have we in this case example shown that simply by virtue of sheer size and exceptional demand on capacity for all technological, scientific, computational and organizational aspects of the Square Kilometer Array, and if we can be so bold, a similar demand on the thinking that must be carried out to address such massive challenges in a project of this nature, that philosophy is best considered a non-entity? That it has no place? That it should be denied? That it is best forgotten?

Now we are faced with a challenge. If we are to address something as significant as better understanding of something, we are instantly thrust into the realm of the philosophical, and in particular, the work of philosophy — even if we are convinced that adequate understanding can be acquired purely by Feyman's calculations. We can be very, very excited by the prospects of improving the outputs of something about which we have some understanding, but when we are reminded that perhaps our understanding of what we are contemplating is not complete or perhaps inadequate to the improvement task, our reactions vary. Let us consider for a moment the extent and nature of the challenge of better understanding of something when, for example, we already are quite convinced that we understand it well enough, or that we have already achieved what needs to be known and understood. The foundation question here is thus also deeply epistemological, and this terrain is not terribly comfortable for many. Expertise, for example, is based on comprehensive knowledge, or even knowledge that is not common but has been hard-won by exceptional and well-recognized effort. This appears to be particularly true in what we have come to understand as "leading-edge", highly specialized, reductionist scientific enterprise.

123 Nobel laureate Steven Weinberg acknowledges in his thesis "Against Philosophy" (1992) that all science has evolved from philosophy. This is entirely consistent with the view of Alston (2005) who reviews the relationship between philosophy and science and points out that the conceptual skills for carrying out work in both fields are essentially the same. This reflects Russell's argument (1996) that although the objects of study might differ, the rigor of reasoning of philosophy and the rigor of reasoning of science are indistinguishable.

However, Weinberg goes further by making a claim about the relative value of philosophy in relation to science. As mentioned earlier, Weinberg states that philosophy (in his example, the philosophy of science) is a "pleasant gloss" and, as such, is not useful to today's work of science. In addition, Weinberg's laureate colleague Richard Feynman is reputed to have once said that philosophy is as useful to scientists as ornithology is to birds (Pernu 2008), and, perhaps more stridently (and much more difficult to properly source), "Shut up and calculate" (presumably meaning that physicists should stop wasting time on things that will never yield much if anything of value, and get on with the work at hand that we can grasp and already know how to address). Here we should also note that Hawking and Mlodinow claim very early in "The Grand Design" (2010) that the mantle of responsibility for addressing the deepest questions with which humankind has wrestled for millennia — ones having to do with the nature of reality, how the universe behaves, and how did all of "this" come to be (these are the same questions that the Square Kilometer Array aims to answer) — has today fallen to science, in particular to physics (and, I suppose, even more specifically, astrophysics — again in large part by virtue of the Square Kilometer Array as the leading-edge instrument of investigation and [hopefully] discovery at this time). They claim that philosophy has not "kept pace" and is no longer equipped to deal with what science has evolved to be, and what science now generates in terms of knowledge (and this new knowledge is, indeed, overwhelmingly large). They therefore assert that philosophy is dead — a step further than either Weinberg or Feynman.

124 But, as Hawking and Mlodinow also acknowledge, it is not in our nature to be quiet and simply turn the crank on whatever machine sits before us — sausage- making, policy, or otherwise. We are speculative, investigative creatures and exchange ideas of all kinds constantly with others. We can only make informed assumptions about what he may have thought about his own inner dialogue (Feynman 1965), but perhaps Mr. Feynman, in evaluating what people talked about and liked to think about, might have perceived more "blather" than the clear terrain of physics, and wished to urge those who had the mathematical skills and were immersed in the mechanisms of reductionism to simply get on with the work of science. That is — to turn the crank, to calculate. We may wish to know and understand, but there are only so many hours in a day to do this, and we already have superb tools to carry out this work; so, get on with it.

Regardless, exchanging, working on and developing ideas through language (or, perhaps more correctly, through many languages including mathematics, music, and art) appear to be hallmarks of the human species. We do a lot of "things" having to do with tangible objects and their manipulation and use, but we also engage in a very large amount of what Pollio (1974) and Handy (1996) refer to as "symbolic analysis" — the often difficult mental work of dealing with concepts, meanings, justifications, and the relationships among them. Although we are reasonably successful in this venture, symbolic analysis is no easy task, for it has to do with meaning, abstraction, philosophical rigor, and thus epistemic clarification. In other words, the work of philosophy is hard to avoid even if we think it might be dead.

Let us briefly view the work of science from this perspective. We can usefully follow the lead of Collingwood in this regard. Here, it is but one expression of the exchange of ideas. Our knowledge of the history of science does indeed indicate that in the time of the early Greeks, for example, language in the form of poetry or narrative was broadly employed to exchange ideas, and much of this related to what we now think of as the science of the day. At that time, much thought was given to what we now think of as the beginnings of things scientific — hypotheses,

125 examination of variables, the search for causes, deeper understanding — for which clear or factual answers or realms far beyond the limits of our senses that we both enjoy and increasingly know today, and especially the methods we now use to derive them, could not yet be known. They could not be known at that time because humankind had not yet developed a systematic scientific method, refined instruments, or other tools such as a "scientific language" of things like advanced mathematics upon which to rely in order to augment their intellect and employ to build deep and comprehensive knowledge.

The idea of something in all "stuff' that was invisibly small and absolutely indivisible in the times of the early Indians and Greeks is a prime example of this. The early notions of something so tiny and incapable of being subdivided being the basic building block of all physical things that are known through our senses was incredibly prescient and was a logical conceptual consequence and extension of practical experience where what was understood to be both the whole and its parts — in various forms of integration — could be regularly and predictably seen. However, at the time this logical conceptual consequence could not be confirmed scientifically (that is, in the way we now understand such confirmation). And now, with the concept being pushed to extreme conceptual limits (Smolin, 2010) we are again moving far beyond the capabilities of physical experiment into the realm of mathematical analysis, and as we do so we are thrust further into the realm of the philosophical.

Today, advances in science and engineering have permitted us to greatly enhance our scientific knowing at a range of scales from the very small to the exceptionally large such that they almost certainly would not have been imagined by our forebears, even as they contemplated dtomos and squinted as thoughtfully as possible into the clear night sky. The philosopher-scientists of the earlier era had to rely on their intellectual rigor to go as far as they could in their pursuits of thought — that is, with natural limits of their senses and tools used to enhance perception, data collection, analysis, calculation, synthesis, and theorizing, such pursuits into the

126 plausible unknown were through necessity relegated only to the realm of the philosophical.

As clear thinkers and brilliant physicists, Weinberg, Feynman and Hawking argue that the philosophical deliberations of the past, although historically interesting and inarguably foundational to contemporary science especially from the perspective of dedicated intellectual rigor, are no longer relevant to today's scientific pursuit in terms of what are understood to be fact or data, technologies, tools, required abstractions, or analytic methodologies. The extension of thought here is that it is only in the past where philosophical pursuit had its highest value; today, the pursuit is merely viewed as "pleasant" perhaps to be considered as bordering on nostalgia, or, as Hawking suggests, philosophy is actually dead. From this point of view of the chronology of philosophy in relation to science, we might be inclined to agree that these scientists' comments reflect a basic fact: things have changed a great deal since the times of the early Greeks, a gradual evolutionary change in what science has been understood to be coupled with how science has been understood to operate, as mapped early in the 20th C by Collingwood (1960). We have, today, in relative terms, very voluminous, expanding and challenging fields of science where our methods, instruments and tools continue to be enhanced and we continue to plumb the depths and explore the horizons of almost everything we have come to know and are yet discovering — the projects of the Institute for Biocomplexity and Informatics (in terms of Systems Biology) and the Square Kilometer Array (in terms of astrophysics) are useful examples of this.

The relentless advance of today's science and the challenges of all the work it involves does, indeed, seem to require the resources of every collective neuron we can spare. As suggested previously, perhaps this can be seen as a question of the economics of resources of thought, analogous to what happens in our vastly consuming polity: in contemporary society when, for example, we consume excessive amounts of some thing, and as a result, resources supporting that thing become scarce. Those remaining resources are allocated to what are thought to be

127 essentials such as energy and infrastructure, and our consequences are thus often, in the classic example, that the arts suffer, or are "the first to go" (meaning funding is reduced and activity or progress is curtailed). In the company of high quality but financially strapped sculptors and impressionist painters, very good philosophers may end up driving cabs to eke out a living (and it may be that they have to do this in any circumstance, so this may not have been a particularly good example!). But surely, if we have Nobel laureates and other great achievers in science, those who apparently have the best brains in the business of the academy, expressing such ideas about the utility or even the existence of modern philosophy in relation to the advance of science and thus its relevance to scientists and their work which consumes their every waking moment, many would think they must be right — if not absolutely, then almost certainly.

There is a double irony here in the claim that philosophy is not useful in today's scientific pursuit, or that philosophy is dead. First, this type of claim is itself based on carrying out philosophical analysis — consciously or not, and limited or not — by those who offer the claim. How is it logically possible to claim that philosophy and the methods of philosophical analysis have little use or no when the only way to make that claim is to employ philosophical analysis? And I would add: if one claims that philosophy is dead (and should therefore be exorcised from our current efforts and allowed to disappear gracefully into the shadows of the past), how does one reconcile this claim with the assertions of Collingwood that have to do with how we know about and explore our core presuppositions, and those of Russell that have to do with our best rigorous thinking about epistemic clarity? Second, when we encounter the limits of instrumentation and (for example) mathematical analysis and comprehension (Kruglinski 2004) we are faced with the challenge of rational speculation about what could be. Here we are at the threshold of what can be scientifically known, considered, examined, tested and re-tested, and tentatively understood. We are, at that point, at the edge of what science is, and is all about, and we are beyond the capacities of both our instruments and our thinking to understand that science. How can one logically incorporate our leading-edge

128 questions, concerns, aims and deliberations about these things into the idea that philosophy either has no relevance to science, or is non-existent?

Both of these ironies suggest that it is a logical necessity to not only pursue and apply rigorous philosophical thinking, but to conduct an ongoing assessment of the value of philosophy in relation to anything that we pursue. It seems that one must simultaneously embrace and know what one is talking about both in scientific and philosophical terms, for example. This seems a strong demonstration of Russell's thought that scientific and philosophical thinking are the same in rigor and process, and different only in focus or scope of analysis. This logically suggests that it is important to know how, and what it means, to be able to conduct a rational and meaningful assessment that is philosophical in nature as well as be a very good scientist; that is, one must logically know about, be aware of, and be capable of doing meaningful philosophical analysis in conjunction with carrying out the best science possible.

The double-edged counterpoint is also obvious: [i] if one does not know what one is talking about and thus cannot conduct a rational philosophical assessment, any claim about the value of philosophy in relation to anything else has no logical foundation, and is therefore meaningless; and [ii], if one does know what one is talking about and can conduct a rational philosophical assessment, one would inevitably come to the logical conclusion that philosophy has only positive value in relation to pursuit or consideration of anything else. Therefore, against the backdrop of the advance of science (or any other field), it is not logically possible to invoke philosophical analysis to conclude that philosophical analysis either has no value or does not exist. In the case of the question of the value of philosophy to science, then, it is not logically possible to create a sound philosophical argument to make the claim that philosophy has no value (or only historical value) in relation to the advance of science, or does not exist.

129 Another logical extension of these points emerges as follows: if it is the case that we have developed and refined and continue to develop and refine very rigorous tools and methods that allow us to engage in what we understand as the scientific method and to conduct scientific discovery and inquiry, and if in so doing we have greatly expanded our abilities to perceive, calculate, analyze, synthesize, explore and refine to the extent that such tasks consume exceptionally large quantities of our time, energy and resources, it is not logical to make the additional claim that the pursuit of philosophy in science in particular, or philosophy in general, is the equivalent of a "gloss" on whatever "real business" we choose to conduct, or, that philosophy no longer exists. If, in the conduct of contemporary science, at the end of the day we end up not having much time, energy or resources left over to think about or pursue the philosophy of science (let alone incorporate any new developments from this pursuit into what new science and scientific discoveries mean), we cannot logically launch or defend a claim that in such a circumstance the work of philosophy in the pursuit of science now has no value, or that philosophy is dead. This circumstance means, rather, that at the end of the day, we've conducted our business, worked very hard, and defined our very being to create and apply more scientific tools to the scientific method to develop new scientific knowledge. Any claim generated about the value (or living quality) of philosophy has no logical relation to either a lack or surplus of time or energy needed to deal with philosophical work. There is evidence to support a clear understanding of the initial conditions (that is, we have a great deal of "science" in the modern era that does indeed consume huge amounts of time, energy and resources while generating copious amounts of scientific knowledge), but even though we may not have much if any energy left at the end of a day focused on science, there is no chain of reasoning to support the claim that philosophy in such circumstances has little to no value in relation to the tasks and outcomes of science, or that philosophy is no longer.

130 6.3 - Philosophy in the Pursuit of Science

So, given where we have come to at this point in the thesis, let us ask: where is philosophy today in the pursuit of science? I am inclined to think that we have worked ourselves into a vast number of highly specialized and productive but narrow silos, or disciplinary (and even interdisciplinary) boxes, within which absolutely excellent leading-edge scientific work is consistently carried out in a wide variety of fields, including Systems Biology and advanced astrophysics as discussed as specific examples earlier in this thesis. The results of this exceptional work are for the most part extremely valuable to society as a whole (as we well know, many great scientific discoveries and their applications have considerable economic impact, for example), and also to the enhancement of comprehensive, general scientific knowledge. Here we see directly the engines of innovation and a strong potential for societal betterment. That is, the sum total of growing knowledge generated from these silos of scientific and engineering excellence is the equivalent of a global treasure. Deep in the silos of scientific excellence reside and work some of the best brains in the academy whose lives are spent carrying out the best investigative, creative and analytic work humankind has ever achieved — work that is of the highest quality and leads to what we hope demonstrates or at least illuminates best paths to reliable scientific knowledge, plausible scientific truths, and through vast networks of innovation diffusion, even distributed economic benefit and potential for enhanced well-being. The example of the Square Kilometer Array as a vast, long-term global project illustrates this line of thinking well.

From the perspective of the early Greeks, we can presume that the focus and specialization we witness today would be astonishing but still quite recognizable, and the circumstances of today's scientific, technical and organizational achievements and riches would likely be seen as a logical outcome of how they commenced with and carried out their inquiries. How wonderful that we can corral and apply and even grow our intellects and the products of our efforts in this way!

131 How amazing that we could use our same intellects to develop tools, and continue to develop such tools that only enhance our capacities to yield such knowledge, benefits and plausible truths! Would not the philosophers of earlier eras roundly applaud the innovations and achievements of scientists in the 21st Century, and happily relegate their early philosophical deliberations to their place in the history of science and philosophy? Would they not sagely agree with Weinberg and Feynman that their work of millennia past was indeed foundational, has seen its most valuable days, and that modern science truly has no need of philosophy? Would they not agree with Hawking's assertion that, in the 21st Century, philosophy is dead?

The point here of course is that the acknowledgement of the relative value of philosophy in early times and the claim that philosophy is not of much use to science today, or has expired, are not the same thing. This is a crux point of this thesis: that acknowledging a truth about an historical context of human tool development and philosophical pursuit, and then going further to claim that such a truth applies to contemporary science and philosophy, does a serious disservice to rigorous and necessary philosophical thought in the context of the emergence of new science and the ongoing advance of human knowledge.

In this section a broad overview of the current terrain of leading-edge science has been provided. The field of leading-edge science is so very large and complex that, in order to be practical in terms of this thesis, this terrain has been selectively delimited to introductory overview examples of innovations and advancements that both succeeded and failed, the case of the Square Kilometer Array and some related scientific and technological developments, and to the earlier commentary about Systems Biology through my experiences with the Institute for Biocomplexity and Informatics. Interestingly, the first criteria for delimitation have revolved around the notion of how large the projects being undertaken might be (e.g., the scope and scale of inquiry, the potential and anticipated scientific significance and outputs of the projects, the length of time taken to initiate, plan,

132 resource, build, deploy, and activate the projects, the expected scientific lifetime of the projects). Very interestingly, a further primary criterion for this delimitation has turned out to be whether the leading-edge science under consideration is driving the growth of "big data" in relation to contemporary science, medicine and engineering.

This examination of the place of serious consideration of epistemological and metaphysical questions in relation to the emergence of leading-edge science — something we clearly assume and think is absolutely critical in our world — once more reinforces the claim that philosophy is not generally seen as something of great importance. We thus return to asking the questions: why would this be? Does it matter? Does philosophy matter?

Is the sheer volume and pressure of modern scientific work the key motivator for Feynman's exhortation to "shut up and calculate (don't bother me with those questions about meaning)", and for Weinberg's thought that the philosophy of science is, at best, a "pleasant gloss on the real work of science", and something that humans did to occupy their thoughts before they figured out that the pursuit of science itself was the only way to achieve authentic knowledge? Could this explain why Hawking is convinced that philosophy is dead?

As this discussion continues, we shall work to determine where explicit consideration of the philosophy of science might reside with such a monumental undertaking, and thereby break trail to the goal of attempting to understand how the denial of philosophy may take place not only in science, but in other realms.

6.4 - Discussion of Philosophical Challenges of Science

Recently, Alexei Grinbaum (2008) observed that "... [m]ost physicists are unready to venture into what they commonly call 'philosophy": not the familiar solid ground of mainstream research, where a

133 scientifically valid 'yes' or 'no' can always be given, but a shaky and risky field of not-just-science, i.e., of thinking about science. The working physicist rarely makes an effort to comprehend and convey deep conceptual issues that come before any mathematical development in the theory he's working on. Members of the theoretical physics community, including some of the most lucid, sometimes claim that they all work like one person, in unison, and there can be no disagreement between them about well-known physics. This is true, or almost, as far as the mathematical content of physical theory is concerned. It is not true with respect to the meaning of mathematical models or the significance of the underlying concepts. That the claim about thinking in unison is made so often indicates that the theoretical physics community does not fully appreciate the importance and the role of what is dubbed 'philosophy' — of asking questions about meaning".

Grinbaum is here referring to the challenge of philosophical questions in the realm of the Large Hadron Collider (LHC), mentioned previously in this thesis in terms of very large data rates and flows. As in the realms of the Institute for Biocomplexity and Informatics investigating the fundamentals of life and cellular differentiation, and the Square Kilometer Array investigating cosmic magnetism, the origins of the universe, and life on other words — there is little if any "common currency" or extensive dialogue having to do with philosophical thinking with the LHC. Grinbaum is here suggesting that for the most part, at least in the theoretical physics community, not much attention or thinking is devoted to asking questions about meaning. His thoughts are reflected by Anton Zeilinger who contemplates the need for a new epistemology of quantum mechanics by asking: "Why is it that the average physicist hears very little about (deep understanding) during his/her education? Why is the comprehension of the theory very often focused on formalism, while questions that probe for deeper meaning are usually not tackled?" (2006).

Here, Zeilinger contemplates the need for what we might call a more mature epistemology of quantum mechanics. This, I suggest, represents the relatively higher level of epistemic maturity that Grinbaum addresses, and, indeed connects directly with Collingwood's building of bridges linking philosophy with science.

134 A recent example of precisely this move can be found Einstein's paper "On the Electrodynamics of Moving Bodies" (1905), where all relativistic equations that appear in his document had been created as attempts by others to interpret experimental data quantitatively and were already known beforehand. Einstein created the comprehensive set of fundamental principles, the conceptual foundation, upon which the equations of the theory of relativity now stand. Because of Einstein's work, the epistemic framework for these principles is complete, and as a result, multiple interpretations of relativity do not occur. Consequently, no significant philosophical problem is associated with the special theory of relativity. Einstein's work established epistemic clarity.

Zeilinger points out that in the realm of quantum mechanics, however, "we do not have such a generally accepted principle which can serve as a foundation of the theory (and this) is the very reason ... that a variety of different interpretations coexist (which are actually in agreement in terms of experimental results)." He argues that at this stage of epistemic development in quantum mechanics, it is not possible to decide which of the interpretations is correct. "Each interpretation ... (contains) an element which escapes a full and complete description," he states. "If we assume that a deeper foundation (capable of supporting such a full and complete description) is possible, the question arises which features such a philosophical foundation might have."

Here, Zeilinger identifies an underlying challenge for epistemic clarification: if we have multiple observations and experiments (and ways of understanding those observations and experiments), plus initial elements of a formative theory, this is not sufficient in any emerging field of science to automatically generate a complete conceptual foundation that supports those observations, experiments, and initial theoretical elements. It is only a short leap to suggest that considerable difficult conceptual work is required to generate a complete conceptual foundation in such a circumstance (Einstein accomplished this in his 1905 work; this is not to suggest, however, that in using the example of Einstein that only the "lone genius" can

135 successfully navigate the conceptual terrain illuminated by Zeilinger; for additional commentary on the difficulty of this type of conceptual problem, see Este and Kauffman [2005]).

In the realm of what are denoted as holonic Systems, Ulieru and Este (2004) also address central epistemic questions by examining novel multi-agent, virtual, self-organizing software and hardware systems now under development and applied to increasingly complex economic and security problems, for example. Koestler (1968) first used the word 'holon' to describe the elements of self- organizing social and biological systems. Considering what here has been denoted as the holonic enterprise, Ulieru and Este acknowledge that advances in mathematics and computer science technologies today allow us to create both programs for holonic systems and the networks to apply those programs in areas of interest or concern to us, including international security or disaster response. We can think of these networks as unprecedentedly large and complex networks of sensors and computational agents — of which the vast sensor networks and leading-edge systems of computational analytics applied to the deep questions asked by the Institute for Biocomplexity and Informatics regarding genetic regulatory networks related to health and disease, and by the Square Kilometer Array regarding our most advanced cosmologies, are two useful examples. Although very practical in its anticipated utility and outcomes, what one can think of as the holonic enterprise is a self-organizing, virtual, multi-agent, modular, adaptable, artificially intelligent system of systems. Its novelty resides in the fact that it has the potential to serve as one of the major components of a ubiquitous problem identifier and solver.

This seems to be analogous to what Zeilinger has observed: although we have a reasonably clear grasp of the multiple technologies we are inventing, developing and invoking, we do not at this time comprehensively understand what we are creating, what is emerging from what we are creating, or what its full range of implications might be. In this instance, as in the previously examined specific

136 examples of Systems Biology and Astroinformatics, we do not have a complete epistemic foundation or conceptual framework to comprehensively understand what comprises what is denoted as the holonic enterprise. Above and beyond engaging in the specific technical and mathematical tasks that allow what is denoted as the holonic enterprise to be invented and developed, to achieve any hope of comprehensive understanding we are confronted with the necessity of considering what dynamical relationships exist among all the elements we are capable of understanding that underpin this unprecedented development — that is, the new models and new engineering resulting from and co-created with new science. In so doing, we have the potential to move towards a more comprehensive conceptual foundation. However, like Zeilinger, Ulieru and Este suggest that challenging epistemic work is required to do this and move toward a clearer understanding of what they call "theory emergence" in the realm of the holonic enterprise.

In these examples we have illustrated that Rittel and Webber's (1973) "wicked problems" of emerging science and engineering pose difficult conceptual challenges that are directly related to the philosophical components of what we can think of as the new science enterprise.

We are now in a position to suggest that, as with the massive enterprises described earlier in this thesis having to do with the story of the Institute for Biocomplexity and Informatics and the long-term development of the Square Kilometer Array, the fields of quantum mechanics and the holonic enterprise can also serve as specific examples of the general case of the need for the development of a comprehensive epistemic foundation in what we are here denoting as "emerging science". But what does it mean to have this sort of challenge? Is it necessary or even possible to have a complete conceptual foundation both supporting and based on observation, experiment, simulation, and application? Do we even know what "complete conceptual foundation" means? Our everyday way of thinking about this would suggest that the pragmatic answer to both questions is "no," and this way of thinking about an answer may illuminate why philosophical

137 denial is broader and deeper than we might have imagined. Zeilinger, and Ulieru and Este, may indeed be correct in pointing out that in their respective cases there may be a lack of conceptual adequacy to permit comprehensive epistemic clarity, but let us stop for a moment to consider whether this has any deep significance.

Whether or not we fully understand the meaning of the term "complete conceptual foundation", a lack of such a foundation appears to be a philosophical problem related to full scientific understanding within an emerging field; but, this does not appear to be a technical or political obstacle or problem in relation to achieving some degree of increased understanding — and significantly, we can readily observe that it is within the realms of the technical and the political where we are the most capable: our most notable and noteworthy achievements appear in these realms. Einstein among many others observed that most philosophical problems, although of significance and even considerable interest, seem to be of the sort that never brings us to what we think of as an answer, but only more questions. On the other hand, we can almost always figure out a reasonable way to achieve something through new technologies or political influence or a combination of the two. We can get somewhere, we can achieve goals, and we can make measurable progress with our technical or political tools without having to rely very strongly, if at all, on conceptual tools for epistemic clarification that might permit us to address philosophical questions. It seems that questions of philosophy, therefore, remain distant from innovation and the advancement of science.

As Mokyr (1999) states, much of human progress (when measured in economic development and output terms) can be attributed to what he terms prescriptive knowledge. This is knowledge we glean from experience as we learn patterns of behaviour and consequence through observation. Prescriptive knowledge allows people to generate comprehensible instructions about how to achieve outcomes or get results without any need to know "what", or more deeply, "why". What Mokyr identifies as propositional knowledge — developed as a consequence of discovering and then developing and knowing at least the basic

138 underlying methods, principles or laws — may indeed be an emergent property of assemblies of prescriptive knowledge in any number of fields, and may also be the foundation for what we now enjoy as increasingly refined emerging science and strategies for what we think is innovation to achieve that science; indeed, in the examples of quantum mechanics and the holonic enterprise, we might speculate that the laws and principles we seek, the comprehensive conceptual foundation and therefore the epistemic clarity that encompasses all observed, experimental and even theoretical elements, will come to pass, all in good time. The same may apply to any scientific enterprise, even one as significant for all of humanity as achieving a cure for cancer through the work of the Institute for Biocomplexity and Informatics, or answering the most fundamental questions of cosmology through the Square Kilometer Array.

The question therefore becomes: if we are reasonably successful in the scientific enterprise (and in the parallel engineering enterprise, and in the enterprise of creating and developing our organizations to support such science and engineering) and continue our efforts with experiment, simulation and theory building where we can achieve our tangible and very useful results, can we not reasonably expect that deep propositional knowledge (if we care to think of it) will eventually emerge? In other words, will the comprehensive conceptual foundation and therefore any epistemic clarity we might come to think we need not simply take care of itself, and eventually appear from whatever mix of "wicked problems" happens to present itself? If we devote virtually all of our time and energy to what is needed, what is exciting, what is new, and how to achieve these things, would it not therefore be safe to assume that the pursuit of philosophy will take care of itself— or, perhaps, that it is simply unnecessary?

Let us be very cautious, for here lurks the most insidious problem, hidden in the shadows of spectacularly grand challenges and similarly grand accomplishments. Although eventually we will tire of engaging in nothing but the discovery of prescriptive knowledge that may at some indeterminate future time

139 lead to propositional knowledge, we may at the same time be mistaken to rush to the conclusion of equating propositional knowledge with a comprehensive conceptual foundation, and therefore a clear road to epistemic clarity. Even if we are not exhausted from expending so much of our energy in our pursuit of science, our tendency to be pragmatic may lead us to commit the error of mistaking the experience of uncovering reliable propositional knowledge based on our observations, experiments, simulations and (compartmentalized) theory generation as either "more or less adequate" conditions, or even the necessary and sufficient conditions, to support plausible conceptual adequacy and epistemic clarity. Even more seriously, we may be tempted to ignore the error and commit one that is even worse: we may substitute propositional knowledge for conceptual adequacy itself. If it matters to us, we may convince ourselves that we are engaging in important philosophical work when this is not the case.

Taken even further, we may not care, or not even be aware of this. We may avoid and then forget about philosophical work altogether as we continue to work very hard on developing reliable prescriptive knowledge and reinforce theory- building and theory emergence with what we create as propositional knowledge from the pursuit of our endeavours. This may be one of the critical steps on what I take to be the downward spiral of self-reinforcing philosophical denial. It may be the case that the words of Hawking, Weinberg and Feynman, for examples, are clear markers on that spiral.

These first steps of denial can therefore be thought of in terms of conceptual slippage. This type of conceptual slippage is of great concern in the emergence of new science as well as all other areas of advance and enterprise, for it speaks to the potential to commit veiy important conceptual errors that can lead to forgetting and then the eventual denial of philosophy. If reinforced and deeply embedded, the absence of philosophy may be then ignored or not even perceived. It may be that on the downhill spiral journey, philosophy migrates into the quadrant of the Johari window where no one knows what they don't know, and will never have any

140 awareness of this whatsoever. It is no exaggeration to suggest that this has great significance in the context of how we then actualize emerging science in our organizations and diffuse scientific innovations throughout our cultures.

In the next section of this thesis, let us briefly turn to the fields of innovation and organizational policy to illustrate why this concern is strongly justified.

141 Chapter 7 - Absence of Philosophy in Innovation and Organizational Policy

In the previous sections of this thesis we have explored a plausible relationship between the emergence of leading-edge science and the role of epistemic clarification in particular and of philosophical pursuit in general. We have explored an overview of major innovations, a new institute at the University of Calgary called the Institute or Biocomplexity and Informatics, and we have reviewed comments about discovery science in the realm of the Square Kilometer Array. We have briefly considered critical commentary about quantum mechanics and what have come to be called holonic systems. We have seen that conceptual slippage in the face of challenging conceptual problems has the potential to seriously endanger philosophical thinking and even the future of philosophy. We have seen claims that philosophy is useless or dead put forward as plausible self-reinforcing evidence for this slippage which, it has been proposed, could be indicators for the eventual final denial of philosophy in general.

In the preceding sections of this thesis we have focused on the emergence of science in relation to epistemic clarification, and in the process have made mention of innovation and the organizations within which these things take place. In the following section of this thesis we will first examine what innovation is or might be, how innovation as contemplated fits into what one might at first very broadly call the "human scheme of things", and how we might enhance or improve innovation by virtue of its membership in this scheme. This examination will lead us to consider where and how the essential work of philosophy — epistemic clarification as underscored by Whitehead and Quine — plays a role in our consideration of innovation.

In the subsection of this thesis that follows, we will attempt to understand what we tend to denote by the term "innovation".

142 7.1 What is Innovation?

Prior to the analysis that follows in this subsection I will utilize the following conceptual framework to anchor our understanding of innovation.

In accord with ideas put forward by Kuhn (1962), Nersessian (1990), Kelley (2001), Rogers (1983), Hesselbein and Johnson (2002) and others, innovation is understood by this writer and specified in this thesis to always be comprised of the following four components or conditions:

(i) the development of a new idea (e.g., a new way of viewing or understanding things, a new process for doing things, or a new tangible product) based on and originating with the convergence of antecedent information and conditions contained within a knowledge system, where the nature of such convergence has to do with some variety of analogical and abductive reasoning concerning the components of the information and conditions in that system; and

(ii) the transformation of that new idea through stages of reformulation and refinement into a prototype (which may remain entirely conceptual, or may also be expressed in concrete terms) which can then be tested (and re-tested in a loop of reformulation where necessary), resulting in a final "proof of concept" prototype; and

(iii) the refinement (and duplication where appropriate) of that "proof of concept" prototype [conceptual or concrete] into a new product (essentially, the creation of potential or actual multiple copies of the "proof of concept" prototype] capable of (i) ongoing refinement as necessary; and, more importantly, (ii) being diffused and shared; and

(iv) the diffusion and subsequent incorporation of that new product throughout and within a receiving system (which may or may not be all or part of the system that contained the antecedent information, knowledge or conditions that led to the original idea).

In this subsection we will delimit our understanding of what we understand to be innovation as occurring in human organizations. This is not to suggest that what we will end up thinking of as innovation cannot take place in, for example,

143 ecosystems or immune systems or neural networks — all of the above-listed components of the posited description of innovation can be understood to take place in a very wide variety of systems and their contexts. The point of differentiation being made here is that we focus our exploration on human organizations that are characterized by conscious intent, and do not include those that are governed by extant default structure or emergent process. That is, if we end up thinking that opportunity and circumstance (which we shall define as a situation that provides avenues for decision and potential action with a probability of allowing the organization to move into a more beneficial environment, for example) help us understand the antecedents to innovation in any system, we will also move in the direction of thinking that the intent of conscious, communicating human social actors will be the determining factor in understanding something useful about how we decide to act in human systems, where such action both continues to shape those systems and leads to what we will come to think of and understand as innovation and its outcomes.

Assumed at the outset is that what we have come to understand as innovation takes place within and in fact itself partially defines a very general model of a complex adaptive system. This is quite significant in that firms, jurisdictions, societies and countries — amalgamations of human organizations that appear to embrace enterprise, productivity, adaptability, proactivity, return on investment, quality of life enhancement — are arguably learning organizations. This suggests that innovation is a feature of any learning organization, and conversely, that it might be quite difficult to think of how one could have a learning organization without innovation; further, this therefore suggests that the degrees of success of learning outcomes of an organization such as a jurisdiction might plausibly be related in a causal way to the extent, nature, character, frequency, import, and impact of its innovation capacity and outputs from that capacity. This harks back to the contrast with Quine's pitiful creatures that are incapable of good inference and are thus soon to expire, versus those that we have already quite handily termed

144 "post-Quinean" in that they learn, adapt, self-modify, and very much survive to live another day.

So, this becomes a rather interesting architectural description of what we continue to explore in this section of the thesis. Some of this will be constructed from what we have come to know about organizations and their jurisdictions, and will therefore rest in the organizational policy realm. Other parts of this map will be constructed from what we claim to have come to know about what we call innovation. The utility of the map will be related to what we can think of as the design intent of this thesis, namely, the initial shaping of an answer to the formative question, "Against the backdrop of the exploration of philosophy, how can we enhance our understanding of innovation in order to have better enterprise, productivity, adaptability, proactivity, return on investment, and quality of life?"

This section of the thesis explores two interrelated fundamental situations, or circumstances, that I believe describe philosophical problems in the epistemology of innovation.

The first is that we do not possess a theory of innovation, especially in relation to how organizational policy processes support and enhance innovation. Assumptions are generally made that such processes do support and perhaps even enhance innovation, and although we do seem to have evidence for some correlation, the connections between cause and effect in these two realms are not particularly clear (see Rogers, 1983; Frenken 2001; von Hippel 1988). But why should not having a sound theory of innovation be considered to be a problem? And what kind of problem would it be? Some might think that having no sound theory of innovation is not a problem if we are both secure in what we believe to be knowledge about how and why what we think of as innovation takes place, and at the same time are convinced that the current state of affairs is simply evidence for the ongoing normal plausible evolution and possible emergence of such a theory (should this state of affairs ever be questioned); that is, some combination of

145 theoretical, practical, and epistemological work that now appears to take place through the "normal course of events" may suggest that such a theory will eventually see the light of day, that it will take care of itself, and that we really ought not be in any great hurry to move this forward — or at least suggest that we are on a reasonable track to such a thing (again, should this state of affairs ever be questioned).

We might also think in parallel fashion that the current state of affairs is not problematic because, by most common measures of economic benefit resulting from our efforts to increase our return on investment, for example, we do not for the most part find ourselves enmeshed in practical consequences of what we think of as innovation that are consistently or terribly dysfunctional or suboptimal (recent global scale financial disasters, cascading major physical system breakdowns, and industry sector collapses and large-scale governmental interventions notwithstanding). The rationale here would be: if we do not have a theory of innovation, this is normal, it is to be expected, is quite acceptable, and this is not a problem — if we ever get around to thinking that we do need to have a theory of innovation, such a thing will inevitably emerge, eventually, no matter what; therefore, we will all eventually find ourselves to be more or less happy with regard to this question (again, should we ever think about such a thing). And, in the meantime, even if we encounter the occasional regional alarm bell or two and even if we identify weaknesses in our economic sectors that profoundly affect the ability of a jurisdiction such as Canada to innovate more effectively (Nicholson, 2009), it seems we aren't doing too badly overall with regard to what we are assuming are processes of innovation in lower-tech economic sectors, that we are smart enough to identify basic process deficiencies that we can choose to ameliorate — and we can be sure that all of this is taking place with no comprehensive theory in sight

Innovation is a topic of discussion and even serious deliberation and economic analysis, but that discussion is often limited to wordfests that tend more in the direction of the reinforcement of work on relatively arbitrary measures of

146 what are thought to be productivity and balances of trade than thoughtful inquiry and reflection. Our current state of affairs thus appears to suggest that we have decided, by default and with limited critical analysis, that a sound theory of innovation is not necessary, or certainly not a high priority for the foreseeable future to be pursued in earnest

One might therefore wonder how philosophical questions having to do with epistemology and presuppositions are understood to fit into how we actually get things done, how we invent and innovate, and the tools we develop and employ to do those things.

In contemplating these points it would seem reasonable to see what others have had to say about a constellation of such related questions. We find some very interesting comments, and 1 will note here that it is not necessary to engage in anything that might be construed as "reading between the lines" — interpretation, of course, but not vacuous construction. For example, the macroeconomist Brian Arthur (2007) recently made the observation:

"Standard economics is rigorous analysis based on faulty assumptions."

This is a pointed comment offered for our consideration by someone who regularly employs every rigorous methodology in the field of economics that can be mustered — and has developed new and significant theoretical frameworks enriching the study and understanding of economics. This is all well and good, but Arthur's comment suggests that rigor — and here we can presume to include rigor of every kind (conceptual, technical, mathematical, scientific, etc.), no matter how well learned, developed, applied, and modified — does us little to no good whatsoever if the objects of that rigor have not been well considered or understood. This would be akin to Aristotle's archers being the best in the world but never being able to knowingly hit a target — hitting an assumed target in the dark with arrows launched by the world's best marksmen is essentially an exercise of chance.

147 Arthur generalized his claim beyond the realm of economics. He went on to say that the phenomenon of rigorous execution of hard work based on faulty assumptions permeates the foundations of most disciplines, severely constrains critical reflective thought and the potentials of disciplinary and interdisciplinary inventiveness, and that addressing faulty assumptions ought to be the primary goal of scientific exploration and refinement (a category of approach to the exploration of knowledge in which Arthur happily included economics).

At this point we can tentatively conflate Arthur's and Whitehead's claims and offer a new one: to not critically examine the assumptions that comprise both the foundation of rigor and the tasks to which that rigor might be applied results in much hard work that might produce a burst or two of progress, but ends in "sterility" — literally, the inability to reproduce and carry on.

Based on the course of the thesis to this point, the question then arises: how does one go about successfully addressing assumptions?

One possible answer that is quite interesting given the purpose of this thesis is: not through philosophical pursuits — at least according to some leaders of industry. Franz Dill (2007), at the time director of the Global Innovation Group of Procter & Gamble (P&G), offered a very serious and powerful assertion, expressed with some strength and pride, almost as a statement of accomplishment:

"Procter & Gamble does not have a philosophy department!"

Mr. Dill's clearly explicated point was that Procter & Gamble is a very large (global), longstanding, reasonably successful and profitable supply-chain management company, and it consistently and successfully innovates — and it has very limited interest in understanding innovation from a theoretical perspective, and most importantly, none whatsoever from a philosophical perspective. Instead,

148 Procter & Gamble's primary interests reside in the what they believe to be tried- and-true "tools of the trade," the technical capacities and techniques to expand markets, product lines and profitability, including such things as improved algorithms that would emerge from applied mathematics designed to enhance the practical methods by which Procter & Gamble maintains and hopes to improve profit margins.

Mr. Dill specified that Procter & Gamble's innovation group was very interested in simulations — something along the lines of "SimCity" (perhaps, as he suggested, "SimSupplyChain") that would permit Procter & Gamble strategic planners and decision makers to apply modern gaming technologies to shave fractions of a percentage point from their costs. "We know that it is very important to understand what innovation actually is — this is fundamental," said Dill in a following small group conversation, "and we know what it is. It's how to make business better to improve competitive advantage. We just want to get on with business, and innovate to do business better." Innovation for Procter & Gamble is based in the refinement of the tools they use, and, where possible, the discovery, development and application of better tools. Their view of innovation is grounded in the nitty-gritty of "the business of business". According to Dill, Procter & Gamble sees very little to no value in pursuing any "why" questions about innovation that do not have to do with improving the tools they employ and the profit margins they aim to expand. Marketplace success for Procter & Gamble is measured by quarterly profits generated only through improving product quality, enhancing sales, and improving service — and the formula for that success is clear. From Procter & Gamble's perspective, epistemological and metaphysical questions might be accurately described by Mr. Dill and his innovation group with Einstein's description of an aspect of quantum theory: "spooky action at a distance" — and the greater the distance, the better. In other words: for Procter & Gamble, choosing to leave their known tools behind and move into the realm of philosophy to enhance innovation would be downright weird and border on the incomprehensible. The tasks and technologies of making money are already clear; and, the pursuit of

149 philosophical questions — even those having to do with innovation — is very hard to justify to shareholders.

The perspective illuminated in the above commentary is no different from that apparently held by corporate giants in the High Performance Computing field13. The "culture of innovation" in these representative industry examples is a constellation of focused technical skills and advanced knowledge, expertise, and judiciously applied political will that supports focused technical refinement and management, and political networking to support that refinement None of this includes any goal of working towards or attaining a comprehensive theory of innovation — even if such an achievement could conceivably lead to better understanding of how to improve processes of technical refinement and managerial and political networking. Procter & Gamble's (and the High Performance Computing players') understanding of return on investment has to do with tools and their improvement, not knowing what a theory of innovation might be, or how such a thing might improve what they fundamentally seek. Resource allocation for research in large firms therefore supports research and development in a focused technical and financial sense, a realm where technical and political metrics are clearly understood, tools can be developed and applied, and performance and productivity can be readily measured. Let us parse Maslow's common aphorism about the hammer and nail at this juncture: "If the only (perspective) you have is (innovation = technical refinement), pretty soon (all your innovation tasks) start to look like (technical refinement)." In the realm of major industry, it seems there is no need here for any other view. The point is: we can get along, and even do quite well, thank you, and discover all manner of new relationships among data points, for example, without any theory of innovation. And we certainly don't need to cloud the picture with any consideration of philosophy.

13 NDAs (non-disclosure agreements) now in place prevent identiflcation of speciflc firms, personnel, or commentary.

150 Interestingly, this possibility is in line with suggestions made by Anderson (2007) who argues that in the current era of extremely large data sets having to do with just about everything we encounter and experience, what we have come to understand as the scientific method is now obsolete. This may at first blush seem rather shocking, especially given my introductory comments that underscored the essential nature of the scientific method as a basis for all inquiry, and how we generally take reason and evidence as being the twin pillars of understanding. Therefore, given what has been discussed about the "death" of philosophy, for example, the claim that the scientific method is no longer necessary for the advancement of science could also be heard as a very strident alarm bell. But, Anderson does not address this concern. Simply put, his argument is that we don't require theory to advance knowledge and extract benefit from its outcomes. All that we need to do, and will ever need to do, is draw correlations from collected data. If this means that advancing knowledge only involves what it takes to find correlations among data, he is arguably correct — and of course, it is possible to find new correlations, especially as we collect increasingly large volumes of data and employ ever more-sophisticated algorithms to sift through those data to find them. However, whether finding reliable correlations in vast oceans of data is good science, or relegates the scientific method to the garbage heap, or whether finding correlations is indicative of good thinking, are separate questions entirely.

From Anderson's perspective, working to develop or even having theory, or pursuing a line of reasoning to reach a plausible understanding "why", is not required — and this should remind us strongly of the computer programmer who ignores and forgets the fifth "W" of programming, and persists in achieving the goals of excellence in programming solely for the sake of programming. Spending time and energy to build theory is not productive or useful, suggests Anderson. Theory, and therefore the scientific method, is not required to decide what we should do. We need only to understand that a relationship among certain variables can be reliably demonstrated to exist, and discovering new ones through massive analytics is all that is required to define what we know. In Anderson's world, knowing a correlative

151 relationship exists is all that is required for success — we do not need to understand what the relationship means, or what it represents, how it works, what the context might be, to develop and test hypotheses or by virtue of any theory building, or to know what it means. Knowing the correlation — and finding other correlations — is sufficient Regardless of whether or not Anderson's claim fits neatly with and reinforces Hawking's argument that philosophy is dead, or whether the two have unknowingly joined forces to do great damage to the rigor and clear thinking necessary to build a sound relationship between philosophy and science, or if the ostensible pursuit of admittedly very challenging contemporary science defined as correlation-finding justifies the claim that philosophy is not required, is not at all clear that only reliably uncovering correlations is good science. And we should recall that Thompson (2009) also asks a similarly provocative and related question: "Does an over-reliance on machine memory shut down other important ways of understanding the world?"

What, then, is our current state of affairs — and why would we be inclined to not give much conscious thought to the development of a theory of innovation that would fit the pursuit and advancement of science as well as epistemic clarification? Part of the answer, I claim, is that we collectively tend to focus on short-term goals and "quick fix" actions regarding methods and outputs of a loosely and incompletely conceptualized set of elements that we think and wish to believe adequately describe and deal with relatively simple actions having to do with how innovation, organizational policy, and economic output are related, and how they can be manipulated for shaping innovation and (in principle) enhancing innovation output I here characterize this as a type of fixation expressed in terms of valorization, the rationale for which 1 would argue is less than well founded. I also question whether this is a desirable state of affairs, and whether we ought to improve upon it

Here I think we have strong evidence that we suffer from a type of compounding of conceptual inadequacy regarding the allocation of our own critical thinking resources to such things as our apparent passive acceptance of an absence

152 of theory in the realm of innovation, for example. I am here suggesting that such self-reinforcing conceptual inadequacy is fundamental to the erosion and eventual denial of philosophy.

1 am here further claiming that the state of accepting or adhering to "non- theory" is not simply correlated with posited conceptual inadequacy. I suggest here that the posited conceptual inadequacy sets the conditions that generate, support and perpetuate the eventual denial of the posited conceptual inadequacy, and thus the denial of philosophy. I am thus here suggesting that generating the claim that philosophy is not required or is dead is, ironically, potentially fatal to the very endeavours that we so fully embrace and into which we think we ought to pour all of our capacities, time, and energies. This seems to be the basis upon which we erect our claim that the crumpled corpse of philosophy should be immediately dispatched to the graveyard.

Therefore, here sits a proposition: if our conceptual inadequacies were reduced, essentially as a consequence of "raising the bar" on understanding what we ought to apply as reliable criteria for determining what are necessary and sufficient knowledge conditions to more completely grasp the interrelated terrains of emerging science, innovation and organizational policy, could this in turn provide us with the opportunity to acquire an improved understanding of what we have come to think of as innovation, and especially, the complex organizational policy processes that support innovation? Could this then lead us to more productively shape and perhaps even improve the processes and outcomes of what we hope to achieve with an enhanced innovation and policy terrain in support of emerging science? These propositional terms describe a motivation, in other words: that if it was possible to improve our conceptual foundation and skills, we might in turn find that the first problem of not adequately understanding the relationships among science, innovation and the policy process could be somewhat alleviated. I suspect that pursuing this would then provide the opportunity for an increasingly

153 deliberative stance that would be supportive of increasing awareness of and derivation of benefits from authentic philosophical work.

We can explore these two interrelated problems by illuminating the terrain of conceptual inadequacy and fixation, and thereby develop initial steps towards a theory of innovation with what I take to be the presenting conditions that have been here characterized as the "first problem": the knowledge limitations imposed by the default conjoint relationship that has emerged between what has been thought of as (i) innovation (and what 1 will here initially denote as its consequences, or "tool effects"; specifically, the achievement of economic advantage and benefit) on the one hand, and (ii) the organizational policy process, on the other. By using the term "knowledge limitations" here, I mean limitations to what I call "conceptual fluency", which in turn means a restriction (the causes of which are related to denial) on both the number of and extent and nature of relationships among concepts used to understand and think about innovation and organizational policy, and, in particular, the methods of synthesis and analysis by which those concepts and the relationships among them are seen to exist, and are thus abstracted, created, destroyed, held in relation to each other, combined, separated, shaped, modified, and otherwise altered.

By using the term "tool effects" (Tomsic and Suthers, 2006), I am making the strong suggestions that (i) innovation has not, in general, been well understood, but has regardless been thought to be a very desirable tool that can be used in attempts to augment or generate economic advantage (perhaps, in relation to the need for a surgical procedure, viewed in terms of the gross effects of a heavy sledge hammer rather than understanding how the blade a scalpel can have very different effects); and (ii) the organizational policy process, similarly not comprehensively understood, especially in the context of innovation, is fundamental to achievement of organizational governance tasks, especially those that relate to innovation, albeit in some fashion that has not to this point yet been rendered particularly clear. Here, the main point is that because, in general, neither (i) nor (ii) are grasped particularly

154 well, in their default combinations the conjoint relationship between innovation and economic advantage is rendered essentially invisible, is unknown with the exception of its most gross features, regularly generates unpredictable and even problematic consequences (although sometimes we are very fortunate when we encounter desirable outcomes), is broadly taken for granted, and is not deeply questioned. It is this last point that has the most significant implications with regard to the philosophical inquiry of this thesis.

Stated another way (and to utilize a spatial metaphor in a complementary fashion), we currently have a shallow understanding of innovation and the conditions that define its organizational policy context and implications. This relative shallowness appears to be widely accepted as the normal state of affairs, suggesting that comprehensive awareness of and reflection upon innovation and its relation to organizational policy may not be common. In support of this thought, the literatures on innovation and policy previously utilized in this thesis — although continuing to be exploratory and even plausibly explanatory with regard to their respective topics — do not appear to argue in any strong or urgent way about the necessity of clearly explicating this relationship with the goal in mind, for example, of augmenting innovation outcomes. On the contrary, such literatures generally appear to first emphasize the anticipated outcomes of enhanced innovation (e.g., higher and more valuable economic productivity — "this is what we need to achieve!" or "our country has been built on innovation!"); and second, the methods by which this might be achieved which are, for the most part, associated with strategic plans and actions that might be best characterized as outcomes-based and focused on return on investment.

My argument here is that this state of affairs is not adequate either for a more comprehensive understanding of innovation in relation to organizational policy, or, especially, the creation of a sound conceptual foundation for improvement of this condition. Simply put, we cannot aim for improvement or enhancement if we do not know or understand well enough (or better still, in a deep

155 and comprehensive way) what, precisely, it is we might aim to improve or enhance, how to about doing so, or what the full range of our options might be. This means that the circumstances with regard to innovation and the organizational policy processes that support it are by default relegated to intellectual mediocrity and what 1 describe as a commensurate "Sargasso Sea" of advance — things are warmed by the sun, get stirred slowly and go 'round and 'round, but there is little, if any forward movement. This is analogous to the "block program" that supports little if any adaptive (re)combinatorial activity that leads, eventually, to the demise of Quine's pitiful creatures that fail the inference test Things get stuck there, they don't change much, cannot learn or adapt, and in fact in today's world such real oceanographic features turn into collectors for human detritus. Perhaps our ocean of what we think of as our innovations and their diffusions, and the policy structures and process that support them, are not much different

For example, it is not generally thought that there are at least these two discrete and dynamically inter-related components that comprise our object of attention, but only one that may be comprised of relatively amorphous elements that, again, are not particularly well defined, differentiated or understood in terms of detail, dynamics or relationship. The economy of understanding, when measured and run via the metrics used for today's complex multi-state economic performance, doesn't require anything more. I suggest that the default consequences of this situation are less than desirable, and by virtue of this thesis provide a clear example that illustrates that our thinking (having to do with how we allocate resources to explore, understand, resolve and apply what we learn from addressing philosophical problems that have considerable degrees of significance and potentially broad differential theoretical and practical implications with regard to both innovation and organizational policy) is inadequate.

At first glance, the immediate surface of the terrain of innovation related to organizational policy appears to be one of Rittel and Webber's (1973) "wicked problems": it is extremely complex, the terrain may not be clearly understood and,

156 perhaps most importantly, is rife with loose and unclear assumptions. The terrain of wicked problems may thus be in the quadrant of the Johari window where we know we don't know, and we must work very hard to change the status of those things that are the objects of our attention so they more regularly reside in the quadrant where we know that we know. For example, in the "known" quadrant, the relationship between what has been thought to be innovation and its "tool effects", or consequences, are, for all intents and purposes, considered to be relatively simple. This point of view is understandable against our backdrop of reductionist science, where the primary goal, in order to reach understanding and to know that we know, is to simplify as much as possible. Thus, with the economy of understanding that is applied here, simple and elegant is much preferred over complex and messy — if we can achieve and maintain the former, nothing else is required.

However true this may be in the hard sciences and mathematics, it is not clear that this is the case when we are faced with questions of the relationships between what we take to be innovation and policy. Let us think for a moment about reductionist principles applied to the complexity of innovation policy. First, a primaiy cause-effect relation is thought to exist where economic advantage somehow springs from innovation, and similarly, a complementary cause-effect relation is thought to exist where more innovation, or at least the potential for more innovation, is generated from the need for economic advantage, suggesting a type of positive feedback loop. However, the conceptual details of what might constitute this loop are not clearly explicated in the economics, policy, or innovation literature. Arthur's point about rigor being applied to poorly-formulated assumptions illuminates this terrain. This suggests that comprehensive knowledge of this posited (and undoubtedly very complex) feedback loop is not available. Second, innovation is assumed to be critical to the achievement of economic advantage, and that economic advantage cannot be generated without it; therefore, innovation, even if poorly understood in relative terms perhaps on account of its complexity, is thought

157 to be greatly desirable for economic advantage and all the benefits it presumably generates.

Without extensive critical analysis and differentiation, a coarse-grained default reductionist view of this circumstance is essentially that innovation equals economic advantage in the sense that equals means always generates. This ersatz equation can be very easily generated from severely limited assumptions and concepts that are not clearly understood. In terms of philosophical rigor as well as practical implications, this can turn out to be a nasty trap. This very rough equation rests against the backdrop of what I suggest is an unclear understanding of the organizational policy process, and how this process in turn affects and shapes what has been thought to support this rough equation, and a similarly loose conceptualization of innovation. But we do not yet clearly understand the component parts of innovation, its organizational contexts, or what might constitute their results in terms of economic advantage.

It is important to note that an equation — or especially, an object that on the surface appears to be an equation, however it has been derived — has the potential to relax a rigorous and critical approach, especially for those eager to rapidly "get to a solution" and, perhaps with some bravado or sense of urgency regarding the next quarter, "make difficult decisions" because it is thought that survival depends on making the right choices, and that the equivalent of "an equation" demonstrates that the hard critical work and application of rigor has already taken place. We have the algorithm. We know that we know. The code has been written.

Of course all of us are confronted with situations from time to time where we have incomplete information, and we are compelled to decide regardless. But having such an approach as a modus operandi instead of what we hope is an intelligent exception is perhaps not the best long-term strategic choice. As mentioned earlier, if the only tool you have is a hammer, soon everything you see begins to look like a nail (and you begin to act as if this were so); similarly, if the only tool you have is an

158 equal sign, soon everything you see begins to look as though it has the properties of equivalence as defined by that sign (and you begin to act as if this were so, too). I suggest that critically avoiding such "modus operandi" traps is essential to enhanced success in the subject field of the present section of this thesis, namely: innovation and the organizational policy process. The "modus operandi" factor as described is thus one facet of the philosophical problem that confronts this thesis.

To determine if there is more to the default object "innovation = economic advantage" which has to this point been loosely denoted as an equation, we here carry out an exploratory examination of what constitutes this relationship. It is possible that if we decide to conduct serious surgery on our object of inquiry as a result, we will separate the two and excise the equal sign in the process of figuring out if we actually understand equivalence. In this case, this can be seen as risky business — separating component parts of what is commonly thought to be a single if somewhat fuzzy entity has the potential to be dangerous because it is not clearly understood. We must be extremely cautious, for with a misstep, it is possible that the patient may expire, and clearly, this is not desirable. To improve the chances for success in this operation, a clear understanding of background and context of innovation and its "tool use" consequences is necessary. Here, delving into the policy terrain of organizations is essential, for exploring organizational policy will allow us to better understand the context of the relationship we are seeking to illuminate and examine. This type of critical task reflects the main purpose of this thesis, and most importantly, clearly identifies the critical nature of conceptual work with regard to achieving a full grasp of policy work in organizations that will hopefully help us determine where philosophy fits within this mix. The following subsection of this thesis therefore provides an overview of organizational policy.

7.2 What is Organizational Policy?

The emergence of new science takes place in what we can understand as the

159 organizational context - that is, the development and exploration of new science and its consequent applications does not occur in a vacuum. Many scientists may protest that, beyond the seeking of grant funding, they are simply too busy to be concerned much with the relationship between the science in which they specialize and the organizations that support that science, much less provide much time and energy to the philosophical foundations of what they aim to achieve. But here we are emphasizing that human organizations within which science is developed are structured by and in part defined by processes that have to do with policy; therefore, in this subsection of this thesis we will examine organizational policy. The reason for doing so is not only to clarify what organizational policy is, but to also explore how conceptual inadequacy in the policy process is analogous to what has already been suggested regarding the emergence of new science. This is particularly important because the inadequacies that appear to affect both new science and the policy processes also shape and support the emergence of new science and help illuminate what I claim is increasingly missing from the philosophical backdrop to these things.

How can we best understand organizational policy? Policy is commonly seen to be the meta-organiser for most organizations. Downey and Este (1984) point out that policy is the relatively stable generative framework for shaping, expressing and controlling overall organizational direction, providing a comprehensive set of statements and guidelines regarding long-term organizational goals, and determining the allocation of resources to achieve those goals.

The policy process has been understood to be an arrangement of functions that an organization generates and uses to accomplish a wide variety of essential policy-related tasks. These policy tasks include: assessing and monitoring intra- and extra-organizational variables through mixed environmental scanning; conducting ongoing needs assessments both within and without the organization through the use of any number of information systems; developing and reformulating scenarios

160 and engaging in informed speculation to identify plausible futures; developing options and strategic plans to generate policy decisions; conducting formative and summative evaluations of processes and products; formulating and reformulating policy decisions; and, creating and adjusting the structures and functions of the policy process itself.

As Schwartz (1991) suggests, policy can be understood to be fundamentally linked to organizational vision, direction and consequent executive decision-making resulting in administrative articulation and action. Policy is therefore both the lifeblood of and the prime guidepost that reveals the structure and processes of organizational governance. This includes the development, holding and articulation of organizational vision, balancing the executive and judicial branches of government, securing reliable methods of consultation and decision-making, and other important functions such as environmental scanning and the maintenance of government's "corporate memory".

Although it is useful to see policy from the perspective of organizational governance, it is also very useful to seek a clearer understanding of what elements comprise policy. Isomorphic with the policy process model put forward by Tichy (1983), Downey and Este (1984) suggest that organizational policy has three essential components, or 'strands' which always operate simultaneously and in concert: the technical, political and the conceptual. Each of these strands are described below.

The technical strand. This first strand of policy is concerned with the tools, mechanisms and resources an organization uses to accomplish its complex multiplicity of tasks. This strand is primarily concerned with hardware (tangible things such as objects and tools), software (programs and plans for making the tangible things work), budget (resources to support action and task completion) — and especially, a system of information management stemming from data collected about all objects and processes in the technical realm. The technical strand of policy

161 can therefore be understood as one of the three primary metaorganizers of organizational governance allowing the identification, shaping and activation of goals in the technical realm, and the allocation of resources to achieve those goals.

The political strand. The second strand of policy is concerned with the intentions and flows of decision-making that channel information and shape knowledge from that information (the foundation of knowledge management), and especially in terms of who influences whom, and in what manners and with what consequences, to inform and accomplish tasks. From many perspectives, the concept of the political strand can be seen as founded on knowing, managing, affecting and working within interpersonal, inter-organizational and knowledge relationships on all organizational levels. The political strand is the realm of useable knowledge in combination with leadership, power and influence, and allows the identification, shaping and activation of goals in the political realm of policy, and the allocation of resources to reach those goals.

The conceptual strand. The third strand of policy can be thought of as 'metacognitive'. It is concerned with the organization's awareness of and grasp of its own policy processes in general. It deals with how comprehensively the political and technical strands are understood by organizational actors, and how they relate to and influence each other regarding different species of policy decisions, especially those having to do with the allocation of resources and the evaluation of policy outcomes. The conceptual strand is the realm of ideas, concepts and broadly applied critical thinking about the organization's system of governance which is an integral part of, and allows the identification and shaping of goals in, policy's conceptual realm — and the allocation of resources to reach those goals. Thus the conceptual strand of policy is directly tied to the conceptual-analytic work of philosophy.

The three strands of policy can be independently defined as outlined above, but function in a totally interdependent and continuously interactive manner. For

162 example, the political strand is defined by notions of power and influence, but is also strongly affected by and affects the technical context of the organization. Similarly, and most importantly for the purposes of this thesis, the consequences of combining the political and technical strands may be very strongly affected by how well the political and technical ideas and concepts of concern are understood — conceptually grasped — by policy decision-makers. In other words, none of the three strands operate in isolation from the others.

This description suggests that policy can be understood to be not only the provision of a set of organizational guidelines regarding vision, overall direction and general resource allocation, but also the establishment of relatively stable, interdependent, reliable, longer-term principles of and guides and goals for operation. In this sense, organizational policy is a type of capacity generation framework to nudge, shape and steer a complex adaptive system. From the perspective of Quinean creatureness, therefore, policy is essential to permit those creatures to adapt, learn, reflect, evolve, survive and thrive. When established in a policy framework, principles for direction and plausible alternatives for action do not have to be reinvented whenever an organization is challenged or when needs arise to contemplate overall direction or meta-organization.

At first glance it may be possible to have the impression that the three strands of policy have equal weight or value. It is very important to note that these three strands, although always in existence, interacting with each other and in operation within organizations, are seldom balanced. That is, any one or two strands may be stronger or weaker than any other in terms of overall effect, and these relative strengths and weaknesses change over time. Indeed, this point is central to what is advanced in this thesis.

Dynamic policy structures and processes are fundamental to how organizations are structured and run. Clearly they are also very powerfully

163 generative in the sense that they set the conditions that permit environmental scanning, organizational learning, adaptation, resource allocation, and decision making. Importantly, they provide a foundation for a procedural framework — the "how to" of an organization which permits it to carry out its tasks in a reasonably structured, predictable yet flexible, and self-referential manner. This is particularly important in light of the previous discussion about prescriptive versus propositional knowledge, where it has been argued that we are generally very comfortable with and competent in the prescriptive realm where the need for deep comprehensive conceptual work is not normally encountered, versus the realms identified by Zeilinger, Ulieru and Este, and in particular by Collingwood where comprehensive and difficult conceptual work is essential to support the technical (and, occasionally, political) elements of emerging new science. This suggests that normative policy structures and processes may reflect some dynamics of prescriptive versus propositional knowledge that may be of interest to us.

We next develop a synthesis between the emergence of new science and the policy processes that support that emergence.

7.3 Synthesis

What is of considerable interest based on the above explication of organizational policy is the significance of the conceptual strand in relation to the technical and the political. That is, if one were to consider organizational policy being created and driven almost exclusively by the technical and / or political strands to the virtual exclusion of the conceptual strand, it is possible to think that organizational policies so generated would be driven not by a full and comprehensive understanding of policy variables, but, for example, only by what might be thought to be the most important — or the newest — technical or political input or variables. Such variables may be reflected in the commonality and ease with which we deal with prescriptive knowledge, versus the relative difficulty we

164 experience in confronting and dealing effectively with the conceptual elements of propositional knowledge. Most important here is that the prospect of the development of organizational policy without the balance of the conceptual strand. This is analogous to thinking about Zeilinger's quantum mechanics, Ulieru's and Este's holonic enterprise, discovery science in the realm of the Square Kilometer Array, and shaping and moving forward the exquisite complexities of the Institute for Biocomplexity and Informatics without a comprehensive conceptual foundation that supports the observations, experiments and initial propositional work of "new science". In thinking this way, we may have identified some important structural and process factors in the policy realm that profoundly affect an organization's capacity to innovate, and for the organization to recognize the needs to integrate philosophical work into the work of innovation and developing its products.

Here, a continuing exploration of what we might think of as "architecture of innovation" in terms of organizational policy is developed, built from prior concepts of the workings of innovation. The provision of a new model of innovation is accomplished through a description of what innovation is thought to be comprised of, how it is related to invention and creativity, and especially, how innovation can be understood as a "modern" concept, however ill-thought-out that, without much serious philosophical questioning, has been in the past assumed to somehow be linked inextricably with the provision of economic advantage. We may find out that this assumption remains reliable, but there may be more to the story. The latter assumption in particular is acknowledged in terms of practice and short-term societal and corporate goals. Here in this exploration, emphasis is placed on how, through the policy process, organizations are engineered to work. Most importantly, these initial steps reveal what I suggest are conceptual inadequacies of our knowing what innovation is or what constitutes the policy process within which innovation takes place. This, I think, describes the opaque lid that covers any possibility of a theory of innovation, and thus, any more mature consideration of how epistemic clarification could fit into such considerations.

165 Through this exploration the assumption is made, with regard to organizations, that it is possible to explicate and understand aspects of innovation and their relationships to the shaping and implementation of organizational policy, specifically policy that supports innovation in the realm of science, or what we might term "science policy". This is an important focus for our task because science policy is one of the most significant aspects, or species, of the constellation of public policy engines that comprise human governance.

Let us now pause and examine the context of the practical versus theoretical. Given all of the above, it seems perfectly logical to think that this thesis would be determinedly practical in nature — practical, meaning here, having specific and clear application to generate desirable and perhaps useful results. In some ways this is so; and, this is a very interesting commencement point for us to consider how the surgery will be carried out. Let us think for a moment about why we might think that thinking about practicality is the best way to proceed. Collectively, we desire and appear to seek improvement and an enhanced understanding of our most important large-scale societal processes and structures, and relationships among them. These are the things that humankind has created and continues to shape in order to articulate and advance the most significant goals of governance. These can be described in terms of capacities to accomplish things — things such as societal stability, health, growth, sustainability, adaptability, proactivity, productivity, safety, security, and the enhancement of all of these.

As we humans engage in the wide scope of work that confronts us, as well as the conditions within which we find ourselves, in general we aim for and hope to achieve improvements from all of these things and, when we can, improve the conditions that lead to and support them. In general, we do not seem to come into this world to rest and do nothing, and simply maintain the status quo. More importantly, we do not seem to collectively have explicit contrary aims to disadvantage ourselves, or our fellows, and make things worse. Indeed this would

166 almost certainly constitute working to irrational aims. However, we need to think carefully about the things that we do that are not a match to the aims of enhancement and betterment One might argue that some intended and especially many unintended outcomes related to circumstances of war, poverty, profound economic imbalances, squandering of resources, mass starvation, environmental pollution, and in general any proliferation of serious physical and mental harm that accrues to many suggests that such elements may have a vibrant if not implicit and even autocatalytic life. Many would say that these things are unintended and for the most part unfortunate outcomes of our collective work as humans, and that they provide clear evidence that we cannot assume we understand or can control all features of our environments or our lives. Indeed many if not most of us take this as a truism. The more cynical among us might suggest that these are the "costs of doing business" — here the argument is that we must accept the good with the bad and especially learn how to successfully compete to maximize the good and avoid the bad, thereby, in accord with one aspect of Rawls' Theory of Justice (1971), for example, leaving the bad for those who cannot successfully compete — even if we agree this is not particularly desirable. Still others might suggest that "it goes to motive," meaning that given our present circumstances it is little wonder that, in general, humans in their organizations appear to seek broad, multi-faceted improvements through whatever means are available, some of which unfortunately cause damage through unintended consequences, while others do not (Nicholson, 2009): hence, we may conclude that creating organizational policy conditions that support the emergence and diffusion of innovations — and what people hope will be their desirable consequences, or positive "tool effects" — may simply not require any deep philosophical understanding, or even awareness of such a possibility, or perhaps even an awareness of philosophy or the work it can accomplish. With this line of reasoning, knowing that creating the conditions for more or less desirable "tool effects" appears to work to varying degrees by first adding to what we believe to be innovation capacities, and knowing at the same time how to keep unintended consequences more or less minimized, is sufficient.

167 Here we may have some insight into the common argument that, with sufficient practical understanding (the equivalent of Mokyr's prescriptive knowledge which I suggest is a direct conceptual match to Anderson's argument that the scientific method is superflous), it is not necessary to have any deep philosophical understanding of what constitutes innovation, organizational policy, and the relationship between the two. This is further resonant with the arguments related earlier in this section having to do with the claim that philosophy is simply not required. If we have managed to generate what are thought to be more or less desirable results by virtue of what we have already learned how to do (so the story would go), we do not need to know much more about this state of affairs. If we stumble upon or are unexpectedly given more knowledge essentially as a gift, fine; but expending scarce resources that would for the most part raise questions that appear to have no answers would be seen a luxury that, in our push to achieve more return on investment and more wealth, we cannot afford. This rationale would go further to reinforce the notion that if we must indeed work to seek anything, it would be to know more about how to acquire, and apply and diffuse, more innovation, which according to this view, in turn yields more return on investment and therefore economic benefit This is a direct echo of the words of Franz Dill from Procter & Gamble. If considered in terms of a cost:benefit ratio where the relationship between these two factors is narrowly defined as economic output value, the argument is that seeking to know any more about what it is, what it means, or why it is — rather than how to apply it (and also, how to improve this "how") — is simply not worth it The return on investment is not sufficiently large, goes this story, to justify allocating what few precious time and other resources we have into knowing any more than that. Hence, the chance of finding a vibrant philosophy department contributing value to industry and its outputs is vanishingly small, and this seems to be borne out by the evidence.

This line of reasoning illuminates another very important facet of the philosophical problem addressed in this thesis, namely, that how evidence for how we allocate resources to philosophical problems that have varying degrees of

168 significance and potentially differential implications (that may, in fact, substantially add to our resources) — and even what we take to be evidence — reveals both a conceptual inadequacy as well as an underutilized opportunity to reduce this inadequacy and thereby enhance the organizational policy processes that support innovation — the very intended outcomes, economic and otherwise, that we seek to achieve. This begins to sound very much like reinforcement for the ongoing story of philosophical denial.

In this section we have identified two related philosophical problems that undergird the purpose of this thesis. The first is that we do not yet have a sound or well thought out theory of innovation in relation to how organizational policy processes support and enhance innovation — instead, driven by fixation of uncertain measure of economic output, it appears that we have by default decided that such a theory is not necessary. We now remain locked on to short-term vision and "quick fix" actions regarding methods and outputs of a loosely and incompletely conceptualized set of elements that we think have to do with innovation, organizational policy, and economic output The second problem is that we appear to suffer from conceptual inadequacy regarding the allocation of our own thinking resources that allow us to think adequately about the first problem which, if they were properly enhanced and utilized, might provide us with the opportunity to acquire a much improved understanding of innovation, and especially, the complex organizational policy processes that support innovation. Doing so would, it has been suggested, open the door for useful application of the very thing that much of economic development and innovation claims is entirely useless if not terribly threatening to economic enhancement and advance — philosophical work.

It might be argued that when confronted with such philosophical challenges, we most frequently seem to seek enhanced understanding of such things and express ideas about them through an emergent blend of theory and practice, often explored through simulation, experiment, and some minor degree of risk-taking. Seeking enhanced understanding about the what, how and why of the things that

169 confront us is a non-trivial task: we can argue that, in a literal sense, our future depends on enhanced learning and knowing what to do to improve things; but note here that the concept of improvement generally revolves around the practical: in general it addresses what to do, not what to think or pursue with regard to the "why". Upon closer examination this sounds suspiciously like a somewhat skewed blend of theory and practice; 1 have suggested here that with an emphasis on the practical there is a commensurate de-emphasis of the philosophical. Once again we are returned to a conceptual analysis of return on investment where the practical is valued much more strongly that the philosophical; and this seems consistent with the strong emphasis on valorization, already mentioned. What have we done with our organizations as a result? It could be reasonably argued that we have developed this thing called governance in and among our organizations because we make the collective assumption that, unlike "nature", the organization of human society and thus collective human action is intentional. It will not run on autopilot and simply take care of itself — human organizations are highly complex and generate both intended and unintended outcomes, and they are characterized by human intention, design, and action. We know very well that we make large and small mistakes in governance as well as have spectacular as well as minor successes, and we need to learn from our mistakes to continue to do a better job. As Esther Dyson (2002) has said, "always make new mistakes".

Governance, founded on our emerging theoretical and practical knowledge, is therefore a futures-oriented function as well as a framework for the process of governance in the moment So the questions addressed from the perspective of enhancing practical outcomes include many that have already been considered here: what is innovation? what is the policy process? what are the relationship among their elements? what do we end up learning about the policy process and about innovation outcomes by exploring these plausible relationships? can all three elements and their sub-elements be enhanced by virtue of what we might learn? With these questions in mind, the initial approach to understanding more about innovation and organizational policy is solidly based on the practical — that is.

170 questions having to do with "how can we make use of and apply this understanding for future betterment" are the first filters through which we view the purpose of this thesis, and hope to achieve useful answers. This is in keeping with what has been presented here about how innovation is most commonly envisioned, contemplated, resourced, and activated within our organizations; and, it can be argued, this is isomorphic with the concept of "techne" — the craft-like knowledge of making or doing, or producing an object, based on what we learn. This, by extension, is also based on what we know and understand.

But, the theoretical has already been mentioned, and mentioned as through it has an intimate connection with the practical. How can this be? Doesn't the very fact that our common thoughts about innovation and organizational policy are founded in and relate so strongly to the practical, to return on investment, to outcomes, to what we can learn to how to do things better? Does this not suggest that the notion of "theory" would automatically be relegated to the back seat, to a position of lesser importance? And by extension, that any serious consideration of philosophy would never take place? Let us recall that although the lenses through which we view this terrain determine almost by default a focus on practical aspects of innovation and organizational policy, we are compelled to also remember that is not the only task for which these lenses have been shaped: they are necessarily bi-focal, along the lines of the duality between science and philosophy that has been mapped by Collingwood and Russell. But how well do we see perceive things through this bifocal lens? What this means is the following: seeing the terrain of innovation and organizational policy almost exclusively in practical terms, although undeniably useful, tends to not provide complete avenues for the exploration or understanding.

Here we clearly see the underpinnings and core purpose of this thesis: first, to explore the question of why it appears to be the case that the practical takes precedence, and what this might have to do with philosophical denial; and second, to determine what are the parts that make up the whole of innovation and organizational policy, and what are their relationships, and particularly, why would

171 this be the case? Let us think about the practical portions of the lenses — they permit viewing and thus understanding only of the "W4", the who, what, where and when. They do not address the "fifth W" — the why. This is a coarse way of making the claim that adequate understanding of complex concepts such as innovation and organizational policy, and the relationships among them, cannot be achieved solely through what one might term the practical view — the theoretical is essential to adequate understanding, to lead to the other half of the bifocals.

In the next section of this thesis we will continue in our attempt to determine how philosophy fits into what seems to be our most important goal — to never find ourselves on the "pitiful" end of Quine's scale of creatureness in any of our enterprise.

172 Chapter 8 - Moving Forward

We have to this point considered how innovation and the workings of the organizational policy process have been seen to be a part of the advance and emergence of science. In this context we have first seen overviews of innovation attempts, two examples of the ongoing advance of science by way of the Institute for Biocomplexity and Informatics and the Square Kilometer Array, and two less- detailed but equally important accounts of such advance by way of reflections on quantum mechanics and holonic systems. We have also seen how we may be confronted with a dearth of well-developed conceptual tools and skills for philosophical pursuit as we attempt to innovate, to advance our organizations, and to push forward the leading edge of emerging science. This has raised questions about theory development in the realm of innovation, for example, and about a sharp contrast between focused and highly productive scientific and technical excellence on the one hand, and the simultaneous withering of philosophy in a fully comprehensive understanding of science, innovation and organizational policy on the other.

In reaching this point, we have now begun to approach the deep challenge of this thesis: namely, a closer examination of how philosophy fits in to such a wide range of our pursuits, successes and achievements, and why philosophy continues to be increasingly disregarded to the extent that it seems almost non-existent by virtue of the examples we have reviewed. It seems that historically, before the advent and vast proliferation of science enterprise as we understand it today, philosophy played an important role as a realm of reasonably rigorous thought that permitted us to consider plausible explanations and understandings. Such consideration was constrained by the limitations imposed by the exclusive and non- instrumented use of our senses, our memories, and our reflective capacities. The route we have taken to do this has today brought us to be exceptionally rigorous in our science and our engineering and all that flows from them; this same route also

173 appears to have moved us very far away from philosophy. Today, under overwhelming pressures from science, data, information, and organizational complexity, the role and significance of philosophy has been seriously eroded to the extent that we do not consider it much if at all, and that we may be experiencing the clear and present danger of losing it entirely.

This presents an interesting state of affairs which can be illuminated with a basic question: for whom, and for whose benefit, is the work of science, innovation and organizations that is carried out today? Here I am agreeing with Ravetz (2006), for example, who suggests that the advances of contemporary science and engineering are, in the modern era, not in general well understood throughout society except by those who have the highly specialized knowledge and skills to work in and think deeply about such fields. This is a description of what is commonly referred to as a "stovepipe" view of the world where profound expertise and specialized knowledge can flourish and accomplish great things, but rigorous exploration or reflection beyond the boundaries tends to not take place. So, a second question: is it necessary for those without such knowledge and skills to understand the workings or the knowledge results of contemporary science? There are many answers to this second question, not the least important combinations of which include political, technical, and conceptual factors, but most of them lead to a common denominator: "yes" — at least to some presumably useful extent This has to do with useful interpretations of new knowledge through innovation processes into the broader realms of how we think about and live our lives. Science and its advances in society therefore logically mean something to more than just the scientists who work on and create such advances.

Ravetz suggests through his analysis that a deep understanding of the metaphysics of emerging new science, aimed at developing a comprehensive epistemology of new science, is essential for us to acquire meaning, not just knowledge as a motivation to practical application. But — why meaning, and not just practical knowledge? This is not an unimportant challenge. In other words, how

174 good and how useful can a new contemporary philosophy of science be made to be in relation to what it is we are coming to know, and how we will make use of it? Would such a thing ever take place in our current situation? And even if we decided that a new contemporary philosophy of science integrated with emerging new science and all that is attached to it was itself necessary, how would we know if we had accomplished this? There are some useful initial steps that might be taken here.

In coming to these steps, I will now review the claims of a variety of philosophically oriented scientists and thinkers. I first acknowledge Feynman's analogy and Weinberg's analyses, but here I am not embracing what they seem to mean in terms of the utility of philosophy. In so doing I simultaneously recall a third laureate, Albert Einstein (cited by Salam, 1990), who said,

"[w]hether you can observe a thing or not depends on the theory which you use. It is the theory which decides what can be observed."

Einstein's comment suggests that our work as scientists is not in some way immune to how or why we shape theory; and, we do shape theory — how?

The creation of theory occurs when we are confronted with something new, where, says Peirce (1934) we

"... turn over our recollection of observed facts; we endeavour to rearrange them, to view them in such new perspective that the unexpected experience shall no longer appear surprising."

So, what is a theory in this context? A theory here is understood to be a combination of the presuppositions held by a person that in effect are both the filters and the support for ways of constructing interpretations of the world, where such interpretations account for the unexpected, and allow us to continue in a growth process of learning how to productively engage in such accounting. This suggests very strongly, in accord with Whitehead, Russell and Quine, that work in

175 the realm of theory has a very large, deeply foundational and highly significant philosophical component. How does this work? Let us recall that Lakatos (1978) argues that

"there are and can be no sensations unimpregnated by expectations"

and Laudan (1977) who also asserts that

"[b]oth historical examples and recent philosophical analysis have made it clear that the world is always perceived through the 'lenses' of some conceptual network or other and that such networks and the languages in which they are embedded may, for all we know, provide an ineliminable 'tinf to what we perceive."

Hanson (1970) opines that the effects of such 'lenses' or a 'tint' are unavoidable no matter what it is we might observe, because

"... seeing is a 'theory-laden' undertaking ... [observation of x is shaped by prior knowledge of x."

Let us also go one step further by recalling Dennett's (1996) observation that

"Scientists sometimes deceive themselves into thinking that philosophical ideas are only, at best, decorations or parasitic commentaries on the hard objective triumphs of science ... (b)ut there is no such thing as philosophy-free science; there is only science whose philosophical baggage is taken on board without examination."

It is useful here to also recall that Torretti (1999), discussing Newton's work in developing the calculus, optics, and the rules of the scientific method, suggests

"to excogitate and to phrase such rules ... would be described, in current usage, as a philosophical activity..."

And, we should also recall Searle's (1999) observations that

176 "[b]ecause philosophy deals with framework questions and with questions that we do no know how to answer systematically, it tends to stand in a peculiar relation to the natural sciences. As soon as we can revise and formulate a philosophical question to the point that we can find a systematic way to answer it, it ceases to be philosophical and becomes scientific ... [the] features of philosophical questions ... tend not to lend themselves to systematic empirical research ... [this] explains why science is always 'right* and philosophy is always 'wrong'... [therefore] precisely because we lack established, empirical or mathematical methods for investigating philosophical problems, we have to be all the more rigorous and precise in our philosophical analyses."

So, here we have: (i) Searle pointing out that questions and problems in philosophy are more general, have no generally accepted method of solution, are more conceptual than questions and problems in science, and therefore (he suggests) demand even more rigor and precision than those that are non- philosophical; (ii) physicists Weinberg and Feynman arguing that, history of science in relation to philosophy notwithstanding, philosophy is useless (or at least minimally useful) to the work of contemporary science (which point of view seems to be logically based on Searle's differentiation, but in opposition to Searle's apparent stance); (iii) Einstein suggesting that philosophy even if not quite so satisfying as science is essential to the work of science (which seems to suggest that even if we accept Searle's differentiation, that working in both scientific and philosophical realms is somehow beneficial); (iv) Zeilinger, against the backdrop of exploration of fundamental physical theory, wondering why physicists today are not trained in or at least familiarized with philosophy (which seems to suggest that science and philosophy, once taught together, are now separated, perhaps reflecting the perspective of Weinberg and Feynman, but opposite to that of Searle who suggests philosophy is essential); (perhaps most importantly) (v), Russell arguing that the type of intellectual rigor required for philosophy and for science are indistinguishable; and (vii) Newton, in carving out fundamental approaches to the scientific method, establishing the "ground rules" for carrying out the hard conceptual work that creates the solid foundation of modern physics, rules we apply with full consistency today — but perhaps with a much-reduced recognition of

177 origin, or sense or understanding of cohesiveness and utility, or how modern physics as just one example of contemporary science continuously relies on the adaptive revision of concepts — which is another aspect of the work of philosophy.

The perspectives raised by all who are listed here can be understood as nothing other than metaphysical core presuppositions upon which are built the logical structures of emerging modern physics in particular and science in general. All of this is in direct accord with Collingwood; these ground rules are Hanson's lenses and tints that support the viewing, shaping and construction of theory. And, logic would thus tell us they are therefore the philosophical foundation of science — a foundation that Weinberg argues at an earlier time did its necessary and sufficient work to now allow us to get on with the "real" work of physics but is no longer required, and that Hawking argues is "dead".

We are thus faced with understanding, to the best of our abilities, the extent, nature, and relative difficulty of the essential conceptual work required to delve usefully into philosophical and thus all scientific work and especially all other work that stands on science and employs the principles of the scientific method (e.g., innovation and organizational policy, for example).

We are therefore faced with an interesting philosophical challenge which can be outlined as follows: if what we have before us as "science" and all its derivatives has indeed evolved with and from philosophy as Weinberg, Collingwood and others acknowledge, and if Einstein and so many others are convinced that what we hold as theory is shaped, focused or filtered by our presuppositions (or our epistemic frameworks; that is, what we already hold to be true - even though in the same breath we acknowledge that the work of science is predicated on conceptual analysis and the revision of concepts), then how can we go about enhancing our knowledge of and capabilities for better science, improved innovation, and more effective and supportive organizations? Where can we turn? What are the best steps

178 we can next take to build the link between philosophy and science? How can we best learn from what appears to be a proliferation of the denial of philosophy?

179 Chapter 9 - Understanding Denial and Delusion

The previous sections of this thesis have been structured and presented in the following way.

Initially, a number of significant questions were raised having to with the relative overall importance and apparent relative functionality of philosophical thinking and pursuit in relation to those things we appear to consider as most important Questions explored here have been along the lines of: what is the status of our collective philosophical thinking when we consider how we commonly tend to expend our thinking energy in the pursuit of our endeavours; in other words, to what extent is philosophical thinking and the work of philosophy important to how we carry out our lives? In the current era, why does philosophical thinking, and the work and outputs of such thinking, appear to have such a low status in relation to what seem to be our main concerns and interests? From consideration of this question, can we safely entertain the idea that we tend to deny philosophical thinking and philosophical work to various extents; and, if this is so, why might this me be the case? How can we most usefully think about what the costs might be of denying philosophical thinking and philosophical work? Are we even aware that this situation might exist? Entertaining and commencing the exploration of such questions in this first section opened the door to the possibility that, collectively, we are faced with a very serious challenge that might be best cast in terms of a potentially fatal philosophical problem — fatal not only to philosophy, but fatal to what we appear to have begun to construct as a prosperous world for all. The idea expressed here was that systematically ignoring and denying philosophical thinking and the rigorous work of philosophy may be putting humanity on a collision course with extinction.

In sections that followed, I explored whether or not the primary claim could be supported by evidence. To illuminate this claim and find such evidence, we

180 examined and explored where philosophical thinking and the work of philosophy exists and is thought to exist (if it does), or appears to fit into three realms of human endeavour — realms that we appear to consistently think are very important for how we structure our lives, invest our time, energy and commitments, carry out our tasks, frame and achieve our goals, and in particular, how we accomplish work in order to not only survive but prosper. These three realms were identified as: (i) what we denote, engage and pursue as "innovation", that is, the diffusion and broad implementation of new ideas, goods, tools, methods, and other such things; (ii) what we denote as "organizational policy" and the policy process that we weave and implement in virtually all of our organizations in order to build, maintain, grow, make useful and adaptable, and make strong what we end up doing collectively in terms of governance, allocation of resources, and all types of other systemic societal function including innovation; and (iii) what we think about, do, and accomplish in the realm of science, especially in the realm of scientific advance, in order to successfully explore the advancement all new realms of physics, chemistry, biology, astronomy, etc., in order to construct new knowledge and understanding, build new insights, and achieve prosperity through novel applications and their benefits. We then concluded, first, that it is definitely the case that the work recently done and accomplishments recently achieved in the current era are indeed spectacular and unprecedented, but also that it is very difficult to detect or find a similarly spectacular set of achievements in (or even commentary about) philosophy that would parallel those in other realms. This finding raised the question of whether or not philosophy has any meaningful role to play in the advance of science, the pursuit of innovation, or in how we think about and structure or organizations to support both.

Now, in Chapter 9, we commence the conclusion of this thesis. Here we aim to illuminate the best route to follow to address the challenge of philosophical denial and its potential final disappearance. We stand on the foundation established in the earlier sections and draw together the major strands of this investigation. The concluding fabric of this thesis, comprised of the initial components discussed and

181 examined here examines some interesting thoughts and suggestions raised by a range of thinkers who have pondered the traps and dangers of the denial of philosophical thought in particular, and critical thinking generally. Reflecting the concerns and questions raised at the beginning of this thesis, in the concluding chapters I underscore the core issues and raise the questions: do we have on hand a good example of what happens if we do not pay attention to what is being illuminated in this thesis?

Danny Hillis (1999) and Stewart Brand (1999) independently suggest that our choices and actions create a legacy, and that we have no choice about that The logic of this claim seems unassailable; and the work and actions of these two innovators seems to support what they claim. Each of us creates a legacy regardless of what we choose to do. They suggest, however, that it might be better to leave a legacy more by design than by default — in other words, to thoughtfully, reflectively and deliberatively take care about what it is we shape, create, and leave behind for others who follow. Taking Hillis' and Brand's perspective into account, I write the final section of this thesis to explore the realm of a world without philosophical thought, to emphasize the importance and what 1 take to be the relative urgency of what this investigation reveals, and to suggest what our collective obligations are with regard to it. We are, after all, creating the future by what we both choose and default into doing. So the questions emerge: what can we most usefully learn about how we do and do not carry out good philosophical thinking, and, what is the best type of thinking we can employ to optimize our actions and thus, hopefully, do the best job possible in shaping what comes later?

I suggest that if we do not very promptly embrace and incorporate our most careful and rigorous philosophical thinking into consideration of how our many projects evolve and how our future will be shaped, and if at the same time we persist with philosophical denial to the extent that we may one day have no idea that we were at one point indeed becoming those pitiful Quinean creatures who we met earlier in this thesis, we may sooner than not discover that our course as it has

182 been set to be irreversible — and most definitely is not quite what we expected and thought we had come to know. I can only hope that it is not too late.

Based on our interest in better understanding what goes on with the phenomenon of denial of philosophy introduced here, intimately intertwined as it is with the refinement of human organizational policy processes (which are ostensibly established to support survival and prosperity through innovation in general, and thus the advance of science through exploration and discovery in particular), we have to this point employed an investigatory stance based exclusively on what is best described as a "scientific" approach. That is, we have attempted to consistently stand on a set of assumptions that we have done our best to understand, but are still admittedly questionable, and that we believe have been constructed as rigorously as possible through clear abductive reasoning (reasoning to the best explanation) which are in turn based on sound evidentiary deliberation (where we seek and stand on what we consider to be the best and the most reliable evidence currently available), this approach being a part of what we have come to understand as the scientific method — where we consistently do our best to construct plausible and defensible hypotheses tested through the careful consideration of what we believe to be the best available current evidence, gained through the most rigorous of observation and experiment, all making use of the most highly-refined tools and instruments now available, and thereby build and support the emergence of theory.

Lest this be interpreted as the application only of "the scientific method" to things scientific allow me to point out that I have not argued that the conceptual framework of investigatory rigor embraced here should be applied only to the pursuit of science (or to what we denote as innovation, or to organizational policy and its processes). I am suggesting that the assumptions that underpin the approach followed here have a much more broad and general application to how we interpret, attempt to make sense of, and reliably know the world around us, and our place in it Apparently most of us have no wish and little inclination to find ourselves on the same track as the pitiful Quinean creatures introduced near the beginning of this

183 thesis. We might usefully recall that they can do little if anything to actively explore or learn about their world shaped as it is by their particular Johari window, which, by definition, is extremely limited. We do not seem to wish our world to be closed off either through lack of awareness or abject shuttering, or to be inclined to learn nothing from our experience or what our environment offers, and thus become extinct

So, we can usefully ask — what shall we do to employ our intelligence and hopefully avoid such a fate? We have learned at least to some levels of success how to pursue science, engage in what we think of as innovation, and attempt to shape and run our organizations in manners that allow us to survive, prosper, and achieve the benefits of our science and innovation, apparently to the best of our abilities. This is not to suggest that we could do better. The preceding sections of this thesis have suggested that we have not done a particularly good or effective job of incorporating sound philosophical thinking in these pursuits, and we continue to experience problems with this way of thinking; but, it seems that we have managed to accomplish quite a bit regardless. Are these three approaches to and expressions of human endeavour — innovation, science, organizational policy — the only ways in which we frame our thinking about how we live our lives and pursue our goals and dreams?

Where else do we attempt to do this? Let us consider for a moment what emerges if we take a few steps back from the scientific approach to generating knowledge and human benefit, and begin to think about the question of how we establish and hold on to what we think of as justified true belief in general. Do we engage in any other types of thinking in any other realms ostensibly to pursue knowledge and achieve what we seek? What happens, for example, in the realm of what we denote as religion — the field of belief and commitment that does not rely on evidence provided by science, but instead relies on faith and perhaps as revelation?

184 I raise this perspective because, in keeping with the apparently inexorable evolution and separation of science and philosophy as described by Collingwood, for the most part we seem to pursue a scientific approach to understanding and knowing. Yet at the same time, what we think of as religion appears to play a significant role in how we embrace and think about our world, how we should conduct ourselves, and understand our place in it — in particular, this is so in terms of religious faith. What we take to be religious faith illuminates non-scientific ways in which we establish and adhere to what we hold to be true. And, historically, it seems an understatement that faith and religion have played a major role is how we have come to shape and live in our world. Considering how we appear to attempt to do this in both scientific and non-scientific realms raises the question of how it is possible to come to shape, establish, and hold beliefs about anything at all.

Let us begin this part of our exploration by considering the phenomenon of delusion (see Bortolotti 2010). Logically, delusion denies scientific thinking founded as it is on reason and evidence, especially scientific thinking that challenges and demonstrates the irrationality and destructiveness of delusional belief (in other words, delusion denies the consistent and rigorous application of a "scientific" approach to knowing); in general, therefore, delusion denies reason and evidence that, together, pull the rug out from under and destroys the foundation of a belief that has no foundation in either. Delusion goes well beyond the denial of science and is founded on what we can describe as magical thinking. Hillis and Brand explicitly suggest that we might want to think deeply and carefully about any legacy we leave for future generations that is based on and / or perpetuates magical thinking; Searle and others mentioned in the previous chapter do so implicitly.

I am here taking delusion to be a way of thinking that is mainly comprised of willingly "fooling one's self and engaging in denial without any reflection that would guard against questionable beliefs or faulty reasoning to the extent that one does not think critically or in an optimal manner, does not rigorously engage in the best thinking possible to avoid magical thinking, and is therefore committed to

185 believing and acting in accord with the belief that a proposition or a set of propositions are reliably true, or at least absolutely unquestionable, when there is no valid reason to do so. Delusion is particularly problematic when, at the same time, one is faced with strong and irrefutable evidence that there is nothing but tradition (the unalterable "block program" of Quine's pitiful creatures) or wishful thinking — a commitment to a belief structure for which there is no support in logic or evidence — meaning a commitment to a set of beliefs that is not held rationally and cannot be defended through reason.

When running this kind of "block program" based on denial of reason and denial of evidence, this is of great importance because such a magical (irrational) belief is established as a foundation piece for creating a comprehensive world view and all that goes with it — that is, how we deal with others, how we engage in the pursuit of knowledge, what we define knowledge to be, what the rules are for acquisition and establishment of knowledge, and from this, how we frame our thinking about our place in the universe. What, then, ensures that the denial of reason and evidence can be maintained, flying in the face of rationality? What rules of the "block program" would ensure perpetuation what I have termed "magical thinking"?

No matter what is held up to be true based on magical thinking, we can suggest that the status of objects and processes of delusional thought places them a position of being subject to critical analysis, just as all aspects of human thought and endeavour. However, this is the case only if a reflective and autocatalytically self modifying approach to understanding and knowing is itself understood and embraced, if reflective thought is possible, and if the rules of how we shall pursue understanding and knowing includes philosophical analysis of the highest order. If the highest order metarule of the block program of Quine's pitiful creatures is something along the lines of "No rule of the highest order as defined here that determines the operation and application of all other current or subsequent lower- order rules can ever be subject to analysis, question, modification or reformulation,"

186 then it would be the case that no highest-order rule could ever be approached critically nor rigorously questioned. This is the sort of unquestionable metarule that excludes reason and evidence. Delusion thus not only denies the full rigor and the benefits of critical awareness, reflection, evidence and what we might think of as a "scientific" approach (and which we have now seen is also entirely consistent with a "philosophical" approach), but also denies the logic of systems of analysis and synthesis such as comprehensive civil law and all other types of logical and rational pursuit, investigation, thought and expression of reason and evidence. Denial in this sense ends up fostering a delusional projection of imaginary structure and process onto and into the "black box" of that portion of the Johari window that we know we don't know, but then moves us to create and stand on claims that we do know based on what we believe to be true in that "black box". Delusion is thus an irrational resolution of a "p and not p" contradiction, and the resulting denial is the antithesis of fully open acceptance and pursuit of unfettered reason and evidence, and of the rigor and benefits having to do with both, and especially, how they plausibly work together. Delusion is the creation of a magical substitute for reason and evidence; denial is the engine behind the delusion.

Philosophy is literally the love of wisdom, and this implies knowledge. That is, wisdom requires and is based on knowledge. If rigorous philosophical thinking is the pursuit of knowledge in any field, then it would seem clear that creating and sustaining a belief system founded on delusion — that is, embracing belief without evidence and incorporating denial of comprehensive inquiry — is not an approach supporting the pursuit of knowledge that is consistent with either good science or good philosophy14.

14 Note that Russell in particular argues that the type of rigorous thinking based on rational inquiry that takes place in and is the foundation of good science and good philosophy is the same in both instances. I suspect that Russell's view is entirely correct This suggests that philosophy is very far removed from being the "pleasing gloss on the real work of science" as suggested by Weinberg, and, contrary to Hawking's claim and much more in line with Searle, is very much alive and crucial to science. This also suggests that any argument attempting to equate religious thinking (based on faith and the denial of rational inquiry) with philosophical and / or scientific thinking (both founded on rational inquiry and aimed at exploring and understanding what we don't know) is completely erroneous and illogical.

187 Of course, it is the case that we can be mistaken in what we believe. We can do our best to create a "block program" to which we apply consistent critical analysis, but it is possible that we establish this program not based on the best evidence. For example, we can be very rigorous when collecting, deliberating about and considering evidence and through this exercise construct what we feel confident is a justified true belief (employing optimal reasoning, as Peirce suggested, to the best explanation), but it is also possible that the evidence we use for this can be incomplete or just plain wrong, or our adherence to rigor in consideration of such evidence rests on mistaking one part of the Johari window for another. In such cases it is possible to draw mistaken conclusions and adhere to beliefs that are wrong but have yet to been proven to be so (and we might wish to question whether or not we can actually denote as evidence those things we encounter that are incomplete or just plain wrong; again, see Gettier 1963).

The pursuit and advance of science and all things based on science is founded on the common understanding that what we take to be reliable evidence may always be incomplete and is always subject to criticism, reformulation and re examination, but is also based on the shared expectation that we will consistently pursue, add to and always make use of the best evidence available in order to rigorously test our hypotheses and construct plausible theory. We again hark back to abductive reasoning to the best explanation (Peirce 1934; Harman 1965). However, pursuit of the best available evidence in concert with rigorous abductive reasoning is not and could never be in the arsenal of denial or magical thinking.

We are also faced with the emergence of new technologies that permit new and better (e.g., clearer, more accurate, more reliable) and much larger volumes of evidence to be acquired, and it is the case that in adhering rigorously to what have evolved to be the methods of science (and their derivatives) we will modify and hopefully improve what we create as theoretical frameworks to account for, reflect and continue to explore that new and better evidence. This process may from time to time lead us through what Kuhn (1962) has described as scientific revolutions —

188 fundamental changes in the core presuppositions supporting the science we are pursuing. This would be the equivalent of altering the metarule(s) of the scientific block program which, up until the time of changing the metarule(s), could conceivably have served relatively well in the pursuit of the science that has led to its own modification, expansion and improvement Scientific revolutions as illuminated by Kuhn (1962) and Nersessian (1990) are thus not a part of nor supported in any way by magical thinking, delusion, or denial.

Consideration of criticisms of religious thinking can be helpful here. The denial and delusional thinking that Dawkins (2006) illuminates and to which he so strenuously applies his objections in the realm of religion and faith are, I suggest, not in any way a part of clear and rigorous thinking about beliefs in any realm.

Taking a similar stance, Harris (2004) suggests that the delusional power of unquestioningly holding religious beliefs confounds all other rational human enterprise, and that this is plainly irrational, highly dysfunctional, and downright dangerous.

What, then, is this thing we call faith, understood to exist against a backdrop of and be a core part of religion? How does it fit within an approach to the pursuit of knowledge that is, for the most part, scientific? Religion is based on faith. Dawkins, like Harris, suggests that religious faith is not only irrational but potentially deadly.

Dawkins' argument focuses on delusion — that is, holding and adhering to a set of beliefs about what we hold to be real and true without relying on, reasoning about, or providing any evidence to support those beliefs, and arguing instead that wishing, claiming and believing certain things to be so solely because they are held to be that way and ostensibly have always been believed to be so somehow does two things: (i) creates a self-perpetuating loop that justifies never questioning why this is the case; and (ii) satisfies all criteria for justified true belief in that particular case (e.g., "if you don't understand what faith is, obviously you don't have faith, and

189 therefore the only thing you can do before it is too late is to acquire that faith, and thereby achieve salvation in accord with the meta-rule — you don't need to know anything else").

This is the equivalent of a person or group of persons claiming that they possess a reliable understanding of something that for them resides in the quadrant of the Johari window where something exists as knowledge and is therefore a solid foundation for a justified true belief, but that the only way to gain access to that knowledge and therefore that belief is to not embrace evidence or reason, but hold that belief based on circular explanations, or no explanation whatsoever. Alternative methods of "knowing" are described in mystical or magical terms, such as embracing revelation or "being saved"; and, per the ultimate metarule, such methods of knowing are not subject to analysis, questioning, evidence or reason.

Why would religion be so strongly focused on perpetuation of itself through blind faith to the exclusion of rationality, to engage so powerfully in denial of reason and evidence? In any other realm of human endeavour — science, engineering, medicine, sport, governance, trade, management — we pursue the most reliable evidence possible to rigorously develop and test our hypotheses through any means we can develop, and establish theory consistent with that evidence. We make mistakes in this process, but work hard to correct them. As Williamson (2007) points out

"Since we can mistake the extent of our evidence, it can be controversial whether a given proposition is evidence. When evidence is not recognized as such, it cannot play its proper role in inquiry. If its status as evidence is controversial, it is not part of the common ground in debate. Relying on a premise one's opponents have already refused to accept tends to be dialectically useless. They will probably deny that it constitutes evidence; one's argument will make no headway. As far as possible, we want evidence to play the role of a neutral arbiter between rival theories. Although the complete elimination of accidental mistakes and confusions is virtually impossible, we might hope that whether a

190 proposition constitutes evidence is in principle uncontentiously decidable, in the sense that a community of inquirers can always in principle achieve common knowledge as to whether any given proposition constitutes evidence for the inquiry."

Williamson suggests that what holds a community of inquirers together is a common set of beliefs about the purpose and methods of inquiry, a neutral approach to how inquiry is to be conducted, and how agreement can be reached about what constitutes evidence. This may be so in the cases of scientific and philosophical inquiry, but the lack of agreement in the realm of religion and faith about what constitutes evidence and the purpose and methods of inquiry by default defines more than one community of inquirers who most likely will never meet (at least, according to Williamson). Therefore making claims about truth, what is argued to be justified true belief and its foundation without providing, seeking or examining reliable evidence would be seen as not being a part of the community of inquirers into science and philosophy, and instead to be embracing delusion. Holding only to faith in either or both of these realms would be immediately seen as playing with a deck that contains nothing but cards that have been preselected to support and verify whatever a particular faith claim happens to be — and from the perspective of reason and evidence, this is not playing with a full deck.

But in the realm of religion, making such claims to truth based on faith is seen as fully acceptable (unquestionably so), justifiable (where in fact there is no rational justification at all), and downright unquestionable (where the unquestionable nature of the claim is itself unquestionable). This can be seen, for example, in the 2010 Annual Report of the Vatican Observatory where the matter of authentic, peer-reviewed scientific investigation into the cosmos using the newest of technologies is perfectly acceptable and encouraged, but some things in the belief environment of the church that are termed "relationships" (e.g., the concept of "soul" or "an entity's fundamental relationship to God as Creator") are simply "not accessible to scientific investigation". They are to be accepted on faith and are not to be questioned or investigated. This is evidence for the defining meta-rule that

191 determines what all other rules shall be. This stance makes it clear that according to the Vatican, which I take here to be an example of long-standing institutionalization of a well-established belief system, the rules supporting rigorous scientific investigation are regularly applied within this particular religious belief framework, but only to realms that are approved by that belief system for investigation. According to the core presuppositions and thus the unquestionable and unalterable (golden) meta-rule, no explanation is to be provided about why this is the case, and any pursuit of explanation or lack thereof is denied.

The promotion of unquestioned denial of scientific investigation into the core epistemic framework of the Vatican that is the foundation of that denial is a specific example of well established and historically anchored delusional stance. A conscious choice to embrace, hold and be committed to a delusional belief, in so doing denying that such a stance is delusional because it is based on faith (defined as unassailable), and in particular to engage in and perpetuate delusional thinking about supernatural beliefs (viz. religion) and all that flows from it (i.e., religious wars, persecution, etc.) as Dawkins suggests, does nothing to support the things that humans have the potential to accomplish by way of clear thinking about reason and evidence and applying the highest standards to achieve that potential through the unfettered and critical pursuit of science, innovation, sound organizational policy, and philosophy. Delusion and denial, joined at the hip, prevent this from taking place.

What, exactly, does delusional thinking deny? Delusional thinking denies reason, or evidence, or both, in various combinations either in whole or in part Delusional thinking does not take account of unfettered learning, inquiry or the pursuit of knowledge in any recursively rational way. This is reminiscent of the shutters that can be closed in the Johari window to prevent the light from coming in, or a clear view from being achieved. This does not sound to be a particularly healthy or positively adaptive way of living in the world — especially, I suggest, in the world of today. In the current era, it is commonly believed that we do not want delusional

192 thinking in our environments, and that we will do what is required to reduce or eliminate it We may be able to understand the place of magical thinking in the rituals and past ceremonies of potlatches, the laying on of hands and staring in wonderment at the stars, the aurora or a passing comet — or even into the eyes of the person who would become our mate — but absolutely not when decisions are made around today's board room tables or operating theatres, on our freeways or flight decks, in our laboratories or where algorithms are written to run our most advanced computers that underpin almost everything we do, on our police forces or in nuclear power station control rooms or in our military, and especially not in the chambers of political leadership and halls of government, debate, or what we hope is sober first and second thought where we assume that evidence and reason will prevail. Nor would we wish magical thinking to affect our philosophical deliberations in concert with all of the above.

We strive very hard to avoid becoming Quine's pitiful creatures. We continue to make errors of fact and judgment of many different shapes and sizes in all of these situations and more, and it seems this is a perpetual challenge — but it is also the case that with our best available knowledge, tools, and abilities to think rigorously and critically and use our best evidence, we do our best to prevent and avoid such errors, and thereby learn so we and others do not repeat them (or, at least, we try to not repeat them too often). Fortunately we do not tend to ask denizens of some imaginary parallel world to sprinkle fairy dust on our friends and foes alike so we can rise to the peaks of the highest magical mountain and grandly win the next battle, whatever we might think it to be.

As Dawkins suggests (1997), if we are to successfully climb mount improbable, there really is no way to actually get to the top through some magical process — unless, of course, there actually is such a thing as magic to which we have access and that we can make work in our favor. There is good evidence for sleight- of-hand in many realms, but we do not seem to have any evidence for magic (by virtue of how the term is used in this thesis). In the realm of evolution as Dawkins

193 and other evolutionary biologists have described it, and for science in general, magic is not in the cards — and any requirement for having magic on hand cannot be met except through delusion and denial. Evolution appears to require the establishment of autocatalytic complex adaptive systems, and systems of systems, through the consistently long, hard work of combined elements of chance, selection, reinforcement, and, eventually, system learning when those systems become sufficiently complex as to enable them to make ever more complex systems of systems. If we take it to be the case that reliable belief systems (and thus what we aim to establish as knowledge) can be established through analogous cognitive processes and elements, we would not tend to think of ourselves as achieving the pinnacles of thinking, knowledge and understanding through magic. Nor would be inclined to think we can get there through denial or delusion. Knowledge and understanding evolve as robust components of systems of belief through consistently long, hard work in rigorously defined fields of study and methods of application. This can be accomplished only through clear and rigorous thinking, not by denying evidence and reason, and wishing and then concluding that things (whatever they happen to be) will be so. And clearly this is not exclusive to the pursuit of science only. As Russell and Collingwood agree, along with Searle and others, this includes the pursuit of philosophy; and as we have focused our inquiry here, this means the pursuit of philosophy in the service of science, technology and innovation.

Where do we tend to apply our energies to minimize delusional thinking or ways of viewing and living in the world that are delusional? Taken broadly, schooling as it has been developed and is generally understood today, in terms of being an institutionalized societal function, is founded in large part on the argument that it is not only possible but highly desirable to have as many people as possible in our society, and over multiple generations, acquire and share a relatively high level of general knowledge, to specialize in and even work to build and develop fields of knowledge and their applications where personal skills and inclinations are strong, to have and promote a relatively well-developed and general capacity for critical

194 and reflective thought, and to have as much opportunity as possible to continue to learn and apply that learning both for personal and overall societal benefit (for example, through making collective political decisions that are as well thought out, optimally informed, and as clearly deliberated as possible; and, to shape and run our collective enterprises through optimal means to the best ends possible).

In psychiatry and counselling psychology, the effort to reduce and eliminate delusional thinking is paramount — where the primary goal of such help is assisting with positive reformulation of world view, for an individual in concert with his or her fellows, to be as clear-thinking, open, deliberative, self-critical, self-motivating, and as helpful as possible for self and others. The examples of education writ large and with the sharper focus of counselling psychology, both aimed to help overcome delusional thinking, are founded on an open, inclusive and fully rational approach to knowing about, contemplating, investigating, and living collaboratively in our world. These examples accept that everyone is potentially capable of responding positively to and pursuing knowledge, insight, and understanding, and are based on a broadly humanistic approach to effectively and optimally shaping that world not only for all of us who are here, today, but for all who will follow.

Hillis' (1999) and Brand's (1999) perspectives with regard to legacy and what they claim is important in the ways we conduct our lives illuminate questions about the quality of life we aim to lead today, and what we aim to shape and provide for those who follow tomorrow. They suggest we do this by creating and embracing the promotion of broad knowledge, rigorous critical thought, personal empowerment and collective wellbeing. Such goals are illuminated by examples of such things as universal public education and genuinely helpful psychological support, which they claim are crucial as conscious goals. This includes excellence and rigor in science and philosophy, and all other endeavours. We can readily recognize that other societally oriented efforts and functions such as effective health care, fire protection, community policing, safety and security for goods, resources and travel, environmental sustainability, resilient and dependable information

195 systems, and advanced research to support all of these efforts and functions fall into the same category of what we think of as highly desirable goals for all. They are the most desirable of social goods. The point here is of course that to achieve them and achieve them well in the world today, we require all of our skills, knowledge, and awareness, and especially, clear and unfettered thinking faculties.

The work of science is not founded on magic — the principles and methods of scientific inquiry simply cannot include delusion or denial; the scientific method is a paragon of rigor and no datum we can find is left unexamined. Similarly, the work of philosophy is not founded on delusion or denial, but — like science — is founded instead on optimal reasoning, also a paragon of rigor with no avenue of thought left unexplored. The more general objects, problems and challenges of philosophy are not the same as the more specific objects, problems and challenges of science, but the pursuit of and adherence to optimal reasoning is central and essential to both science and philosophy. If there is anything we can denote as "faith" in how we think about and embrace both science and philosophy, it is that we have faith in reason, and we have faith in our ability to pursue and apply reason in the most rigorous ways possible. By having faith in the processes and products of reason, we aim to achieve an optimal state of justified true belief.

But in this thesis we have also seen that, today — particularly in the realms of emerging science, innovation, and organizational policy — evidence is very slim to non-existent for broad, ongoing, explicit and conscious consideration of questions and methods of thinking having to do with philosophy. This does not mean of course that the work of philosophy does not continue inside the stove pipe of specialization where philosophers do philosophy and think philosophical thoughts — indeed it does, and we ought to be happy for it But, it is not at all clear that the work of philosophy carried out in this way provides any help, guidance, insight or illumination for those who carry out the work of science. We have seen, for example, that scientific leaders who may have attempted to understand the role of philosophy in the ongoing growth of the science enterprise have concluded often with bold

196 pronouncements that science has no need for philosophy. Philosophy has now been separated from science by vast conceptual distances — shuttered from the foci of our scientific, innovation, and organizational interests. Here, our concerns, endeavours, goals and our achievements have little chance of finding benefit from philosophical thought. From all accounts that have been related here, we are well on our way to complete philosophical denial, and then meta-denial. A general denial of philosophy means that we deny the full scope of our capacity for optimal reasoning.

We have also seen in this thesis the notion that faith when founded on the denial of reason raises very serious questions about the acceptance, application and even the conscious reinforcement of delusion. By having faith in the processes and products in a closed system of non-reason, we aim to achieve an optimal state of justified true belief.

So we are confronted with two tracks to establishing what we hope to hold up as justified true belief. One is based on reason, the other on non-reason. Let us examine where either of these approaches takes us.

Let us consider a person who knows nothing about Darwinian evolutionary theory (natural selection in particular) except that, whatever it is, it exists in opposition to religious dogma (creationism is particular); and then, if that person works hard to learn as much as possible about Darwinian theory but simultaneously persists in holding what he or she is certain is a justified true belief in creationism, we have a curious situation of contradictoiy true beliefs — a situation where we might wish to critically examine the type of thinking engaged by that person (if we were in a position to entertain the thought that critical examination would be useful). The motivation for critical examination of this thinking would be to explore the question: how is it logically possible to hold a pair of contradictory beliefs, to continue to hold what is thought to be a justified true belief in creationism when a great deal of demonstrably scientific, reliable evidence and rigorous thinking about that evidence suggests that, over time, a combination of randomness and natural

197 selection have permitted biological evolution to take place, and, in fact, suggests very strongly that life is inevitable without anything like "divine intervention"?

Let us then assume this critical examination is carried out by a second person who we will say possesses a perfect disinterest in the situation, who assesses the type of thinking that the first person has engaged to continue to hold the contradiction by believing in creationism after learning as thoroughly as possible about Darwinian evolutionary theory. What conclusion would be drawn by the second person about the thinking of the first person? The conclusion would almost certainly be that any reasonable, reflective, deliberative person who achieves a reasonably high level of understanding and knowledge about Darwinian evolutionary theory, or any theory for that matter, could not rationally and simultaneously hold a belief in creationism (or some theory that directly opposes the first). This would be the equivalent of holding beliefs p and not p simultaneously. Therefore, by continuing to hold a non-scientific creationist view of life in the face of powerful scientific evidence for biological evolution, the first person would not be seen as rational by adhering to a way of thinking that is logically impossible (e.g., believing that p and not p are equivalent, or do not exist, or through some other way of thinking are not contradictory).

Note that this does not mean that the second person drawing this conclusion about the thinking of the first person could logically in the same breath argue that the first person, having reached a relatively high and perhaps even expert level of scientific knowledge, could not believe in a personal god, for example. That is not what the critical examination of thinking would have been about Rather, the critical examination would have been about whether or not it was logical and rational, based on full acceptance of new, rigorous and comprehensive knowledge, to not shift core beliefs about how life as we know it has come to be and continues to adapt to its environment — that is, to not shift from holding creationism to evolution as a justified true belief to account for what we have learned about and accumulated as evidence about life on Earth. This line of reasoning would be consistent with

198 Einstein's personal comments about what he claimed to be the case with his own science and religious beliefs, where (as recounted by Weinberg), Einstein defined god as his personal understanding of what he denotes the "majesty" of nature as he had come to understand it It is not an unimportant thing to recognize that Einstein, as a brilliant revolutionary scientist, was not unaware of the deep philosophical significance of what he sought to understand, the concepts about which he had insight, the rigor and clarity of what he developed in terms of physical theory, and what these things meant (and continue to mean) for his and our ongoing exploration and understanding of reality. But, as with our example of the creationist who learns evolutionary theory, for Einstein it seems that what he then came to think about what he denoted as god, as he considered it, had little to do with "traditional" views of religion and faith. In other words, although Einstein claimed a belief in god, it was god as he defined and interpreted it in terms of his personal passion and awe for the science he had invented and pursued, and his emergent understanding of the universe and our place in it, all of which was very distant (and, I think, entirely separate) from any traditional religious view.

The fact that in the realm of religion, faith extinguishes and denies the reason of inquiry and independence of thought necessary for such pursuit with regard to any basis for what is believed and held to be true from the perspective of that faith is not seen as important or problematic. The denial of reason and evidence in this realm is not seen as problematic because denial of these things requires faith. Faith appears to be the only widely acceptable delusionary stance based on the rejection of comprehensive reason and evidence. In so many of our realms, delusion and willful ignorance by actively denying reason and evidence, and as a result causing personal, familial or larger-scale harm and destruction based on these things, is, in general, seen as dysfunctional and in almost all cases transgresses all boundaries of legal, moral, and intellectual integrity. Such things are certainly not seen to be desirable or acceptable and are studiously avoided.

199 Yet, the denial of reason and evidence, and the consequent persistence of delusion so evident in the embrace of faith in the realm of religion, is somehow immune to this criticism. Why would this be so? Why are all other realms of our pursuit not immune to this criticism? Why, only in the realms of faith in consideration of religion, are conscious delusion and denial entirely acceptable and, in fact, required and even defended to the point of death? What does this phenomenon of a dual, self-contradictory and simultaneous rejection and acceptance of delusion and denial tuned to very specific circumstances allow us to learn about our own ways of knowing about and understanding the world, and how to live successfully within it?

In this chapter I have attempted to illuminate that faith (or the construction of belief structures or epistemic frames) when founded on denial and delusion, and by extension not founded on evidence and reason, can seriously delimit both what we can achieve and what we aim to achieve. To illustrate this, I have used the example of faith in the field of religion.

But let us be perfectly clear: it is the case that, in the end, we engage in most of what we do based on faith. In the realms of science, innovation and organizational policy, we carry out inquiry and conduct our affairs based on faith in the methods of thinking we employ and the tools we develop and apply. In other words, our world is founded on faith in reason. By definition, we cannot drill down into the foundations of religious faith through rational inquiry and consideration of evidence; however, we are able to drill down into the foundations of faith in the realms of science and philosophy by clarifying, pursuing and thinking as clearly as we possibly can about what Collingwood (Martin, ed 2002) describes as absolute presuppositions. This is the precise focus of the argument that the work of philosophy has great significance for the pursuit of science and, indeed, for the vast majority of our endeavours, and that the denial of philosophy is both a philosophical and a practical problem.

200 It should be patently obvious that I have focused on faith in religion as an example of a realm of thought that is by definition strongly delimited, where thinking about and exploring absolute presuppositions is not a part of the "rule set" that determines any following thoughts. This has been pointed out with reference to the 2010 report from the Vatican observatory, where the clear statement is made that such a line of reflective investigation is simply not available ("not accessible to scientific investigation"); this means that line of pursuit and reasoning does not exist.

But, if we stand on this example and examine our other endeavours, my argument here is that having such a core guiding principle in the realms of either science or philosophy is a trap into which we dare not fall. The problem is, however, given the apparent ongoing denial of philosophy in the realms of science, innovation and organizational policy, it seems we are in danger of beginning an increasingly rapid descent down a very slippery slope headed precisely in such a direction — even though we might hold fast to the idea that the denial of philosophy could never endanger the advance of science and all that is connected to it (I would here point out that believing this to be the case, or having faith in such a way of thinking, suggests that the denial of philosophy is successful simply because anyone who refuses to think that such a thing is possible evidently has not thought through the problem).

If we find ourselves being tempted to think that philosophy is dead, or that the work of philosophy can simply be dispensed with, or if we begin to mistake the work of philosophy for a lack of faith in reason, or, more specifically, a lack of faith in (or even a threat to) the work of science and all that makes science possible, I would hope that the alarm bells would begin to ring at a very high volume. Given what has been related in this thesis, I hope the alarm has now been raised. Denying philosophy and thus finding ourselves increasingly less able to rigorously explore the locus of unsolved (or perhaps even not-yet-identified) problems, and thus perhaps accept an ongoing subtle increase in and gradual advancement of denial of

201 reason and evidence would, I suspect, be a self-defeating proposition. This would be akin to some Quinean creatures realizing that their world is increasingly shuttered, and at the same time finding themselves less and less able to draw inferences to the point where they cannot learn, cannot adapt to changing conditions, and thus become extinct I am quite sure that we do not wish to paint ourselves into such a corner, a literal dead-end. Having faith without reason or evidence that we will not do so, essentially because we are compelled to wish it to be that way, is very different from having faith in our best capacities for reasoning and selecting and making use of the best evidence, supported both by our science and our philosophy, that will help us make reasoned choices to avoid such a fate.

202 Chapter 10 — Conclusion (Philosophy Undenied?)

This thesis has explored the idea of the denial of philosophy in the realms of science, in what we think of as innovation, and in the design and activation of how our organizations are shaped and run. This thesis has also illuminated the denial of philosophy and has utilized for purposes of illustration the denial of evidence and reason in the context of religion and faith. It appears that, for the most part, the pursuit of philosophy is seen as being irrelevant to the vast majority of our concerns about and interests in the world today — whether we focus on realms of human endeavour and achievement where we hold critical thought by way of reason and evidence to be paramount, or if we embrace and focus on a realm of belief based on denial that is delusional. And although we have encountered some encouraging debate about the role of philosophy in relation to science in particular and the types of rigorous thought recognized to be shared between these two realms, we have also seen at least one explicit and direct claim by a renowned scientist (Hawking) that philosophy is dead.

We have now reached the conclusion of this thesis. However, the fabric being woven here is nascent and incomplete — it has only just begun to take shape. In fact, a thesis of this nature when developed to the present level could not be considered to be more than this. However, taking the next logical step from Collingwood's last thesis, The Idea of Nature (1960), the exploration of the denial of philosophy in our most important realms of endeavor has now commenced. This exploration has begun to illuminate what we take to be innovation, a variety of significant considerations in the pursuit and advancement of science, and how we shape and run our organizations to achieve our goals. It appears that a great deal of work remains to be done in the realm of exploring further and dealing as effectively as possible with philosophical denial that appears to be in common with much of our enterprise. I do not believe we can choose to perpetuate the risks of not considering or not making work our generalized philosophical capabilities. I cannot overemphasize the potential significance of what these initial strands of thinking

203 mean in terms of this simple thesis, and especially, what the future impacts of weaving the larger, longer-term fabric of a more comprehensive investigation into the denial of philosophy might be.

We have not come to the end of the philosophical work that, as has been argued here, is essential to improve our lot. But, when we reflect back on the paths taken in this thesis to explore the terrain of innovation, organizational policy and the policy process, and leading-edge science even in its form necessarily delimited for the purposes of this document, we recognize we are currently living in default circumstances that have left what I would call "authentic and useful practical philosophy" in the lurch. This is a very serious state of affairs; and, what I take to be the growing denial (and the meta-denial) of philosophy is of great concern. That is, we appear to have moved into the realm of ongoing recursive denial of the importance and utility of philosophy and its applications. As a consequence, we are in danger of being tempted to think that not only has the job of philosophy already been done and that philosophy is not required, but that any news or reminders that this might not be the case have been are also to be denied.

As is always the case with denial (and the denial of denial), I am claiming that this state of affairs is based on entirely inadequate reasoning and faulty assumptions. And if we are confronted with evidence for inadequate reasoning and faulty assumptions, this situation must logically be remedied. The specter of proliferating denial of philosophy cannot be ignored. This, I claim, is an extremely significant philosophical challenge. Any good scientist who loves his or her work and aims to expand the knowledge of humanity would agree that optimal reasoning and intellectual rigor, strong and reliable evidence, and the best methods and instruments possible are essential to good scientific work and the highest quality of its products, especially to support and make available for critical review its authenticity, its principles, and its findings. As Russell, Collingwood, Searle, Williamson and others have so strongly suggested, the same holds true for any philosopher and the work he or she aims to carry out But the Johari Window

204 appears to show us that the practical future of philosophy may be well on the way to becoming increasingly shuttered and dark, to the extent that it is one day permanently walled up and forgotten. 1 have created the argument here that such a future is untenable.

The closing argument of this thesis therefore has had as one of its essential components the point that the work of science and the work of philosophy are, together, part and parcel of the ongoing pursuit and enhancement of knowledge and wisdom, founded on the same species of intellectual rigor as well as the expansive and growing knowledge we enjoy today. Having faith in reason and evidence to the extent that we can follow a line of rigorous philosophical inquiry to illuminate and for the time being accept our core presuppositions without falling victim to denial or delusion is central to the tasks of science and philosophy. To de-emphasize, misrepresent, deny or entirely leave philosophy out of the models and methods of innovation, organizational policy and the policy process because it is thought to be too general and not particularly useful in the pursuit of the specifics of leading-edge science, innovation and our organizations of today, is a symptom of misguided, misunderstood and incomplete epistemologies founded on unexamined presuppositions. This is a road to expanded denial, delusion and epistemic blindness, a place where 1 hope nobody wishes to go.

This suggests that the extent and nature of what has begun to be explored, argued and explicated in this thesis constitutes essential philosophical work. If we are to ask ourselves "Where it he work of philosophy?" we find that it lies before us as a challenge to refute and reverse the path to its denial.

The concluding stance of this thesis is a clear response to Collingwood's call, to Hawking"s dramatic claim, and indeed to the optimism gently expressed by Searle and Williamson, for example. The realm of this essential work will likely require re discovery of and re-introduction to our most critical of philosophical approaches and pursuits to steer away from conceptual slippage into what we have already

205 begun to paint so darkly. If we do not pursue and generalize what I claim to be essential philosophical work, however, I feel quite confident in my prediction that the future growth of our undeniably wonderful technical, scientific, organizational and political accomplishments will not be sustainable, and will pale in comparison to the significance and long-term impact of our cumulative inattention to and denial of the necessity of philosophy. We cannot ignore the possibility that we are on the route to being post-Quinean in the least desirable of ways.

At the conclusion of this thesis, therefore — and to paraphrase Samuel Clemens (1897) — we might hold up as our goal the proclamation that the reports of the death of philosophy in the realm of innovation have been exaggerated.

206 207 Bibliography

(2010) "About the SKA" < http://www.ska2011.org/About_the_SKA.html > retrieved September 11,2010; < http://www.skatelescope.org/media- outreach/books/science-book/ > retrieved October 26,2010

(2010) "Atacama Large Millimeter Array" (ALMA) < https://science.nrao.edu/facilities/alma > retrieved October 26,2010

(2006) Denying Science (editorial), Nature Medicine 12, 369 (1 April) | doi:10.1038/nm0406-369

(2006) Department of Systems Biology home page, Harvard Medical School < https://sysbio.med.harvard.edu/ >, retrieved 15 Feb 2006

(2010) "Exascale, SKA" < http://www.exascale.org/mediawiki/images/3/3a/Skaiesp.pdf >, retrieved 2 0 November 2010

(2006) Focus Alberta < http://www.alberta.ca/home/documents/focusab2004july.pdf >, retrieved 22 November 2006

(1969) "Go Ahead for the Boeing SST?" Air Transport, Flight International, 02 October < http://www.flightglobal.com/pdfarchive/view/1969/1969%20- %202894.html > retrieved 28 September 2011

(2005) Institute for Systems Biology (ISB) home page < http://www.systemsbiology.org/ >, retrieved 19 Oct 2005

(2010) "Large Scale Synoptic Telescope" (LSST) < http://www.lsst.org/lsst/ > retrieved October 26, 2010

(2004) Lead Editorial, Systems Biology, Vol. 1, No. 1, June < http://ieeexplore.ieee.org/iel5/9270/29451/01334968.pdf?isnumber=29451&pro d=&arnumber=1334968&arSt=+l&ared=+l&arAuthor=+Iyengar%2C+R.%3B++Wo lkenhauer%2C+0.%3B++KoIch%2C+W.%3B++Kwang- hyun+Cho%3B++Klingmuller%2C+U >, Systems Biology online no. 20049001, doi: 10.1049/sb:20049001, retrieved 12 December 2005

(2007) New England Complex Systems Institute (NECSI) home page < http://www.necsi.edu/events/iccs/iccs3program.html > retrieved 18 June 2007

(2002) New Penguin Dictionary of Science. New York: Penguin

208 (2002) News Transcript, Secretary Rumsfeld Press Conference at NATO Headquarters, Belgium. U.S. Department of Defense, Office of the Assistant Secretary of Defense (Public Affairs). < http://www.defense.gov/transcripts/transcriptaspx?transcriptid=3490 > (retrieved 17 January 2008)

(2010) Science, Philosophy, and Theology, in "At the Crossroads of Science and Faith", The Vatican Observatory Annual Report, The Vatican: Vatican Observatory Publications

(2002) The Oxford Companion to Philosophy. New York: Oxford University Press (USA)

(2009) "The Technology" Square Kilometer Array < http://www.skatelescope.org/the-technology/ >, retrieved 13 April 2009

(2011) "Value judgments; The scientific endeavour needs to deliver public value, not just research papers," (editorial) Nature, 123 12 May 2011

Achinstein, Peter (ed) (2005) Scientific Evidence: Philosophical Theories and Applications. Baltimore, MD: The Johns Hopkins University Press

Adams, Douglas (2002) The Hitchhiker's Guide to the Galaxy. New York: Del Ray / Random House

Ajzen, Icek (2002) "Perceived Behavioral Control, Self-Efficacy, Locus of Control, and the Theory of Planned Behavior," Journal of Applied Social Psychology, 32,4:665-683

Aliseda, Atocha (2006) Abductive Reasoning. Logical investigations into discovery and explanation. Dordrecht, The Netherlands: Springer

Alston, William P. (2005) Beyond "Justification". Dimensions of Epistemic Evaluation. Ithaca, NY: Cornell University Press

Altschuller, Genrich (2005) Shulyak and Rodman (trans), The Innovation Algorithm. TRIZ. Systematic innovation and technical creativity. Worcester, MA: Technical Innovation Centre, Inc.

Anderson, C., G. Theraulaz and J.-L. Deneubourg (2002) Self-assemblages in insect societies, lnsectes Sociaux, 49,99-110

Anderson, Chris "The End of Theory: The Data Deluge Makes the Scientific Method Obsolete," WIRED, 16.07 < http://www.wired.com/science/discoveries/magazine/16-07/pb_theory >, retrieved 22 July 2007

209 Ariely, Dan (2008) Predictably Irrational. New York: Harper Collins

Armour, Philip G. (2000) "The Five Orders of Ignorance", Communications of the ACM, Vol. 43, No. 10 < http://losangeles.acm.org/Archives/laacm0512- Article%2002%20The%205%200rders%20of%20Ignorance%200CT%202000.pdf > retrieved 19 May 2004

Arthur, Brian (2007) Opening keynote address at IBM's Alamden Institute, San Jose, California, April 11-13. Arthur is a professor at the Santa Fe Institute, inventor of the theory of increasing returns, and Visiting Researcher in the Intelligent Systems Lab at PARC in Palo Alto

Auyang, Sunny Y. (1998) Foundations of Complex-system Theories in economics, evolutionary biology, and statistical physics. Cambridge, UK: Cambridge University Press

Bak, Per (1996) How Nature Works: The Science of Self-Organised Criticality. London, UK: Springer-Verlag London Ltd

Bateson, G. (1979). Mind and Nature: A Necessary Unity. Advances in Systems Theory, Complexity, and the Human Sciences. Hampton Press: New York

Beiner, Ronald (1983) Political Judgment. Chicago: The University of Chicago Press

Bock, Walter J. (1959) Preadaptation and Multiple Evolutionary Pathways. Evolution, Vol. 13, No. 2

Bortolotti, Lisa (2010) Delusions and Other Irrational Beliefs. Oxford, UK: Oxford University Press

Brand, Stewart (1999) The clock of the long now: time and responsibility. New York: Basic Books

Brand, Stewart (1994) How Buildings Learn; what happens after they're built, Penguin: New York

Brockman, John "Edge" < http://www.edge.org/memberbio/john_b >, retrieved 08 June 2009

Bumiller, Elisabeth (2010) We Have Met the Enemy and He Is PowerPoint New York Times < http://www.nytimes.com/2010/04/27/world/27powerpointhtml7hp > retrieved 09 Oct 2010

Burke, James (1999) The Knowledge Web. New York: Simon and Schuster

210 Calvin, William H. (2002) A Brain for All Seasons: Human evolution and abrupt climate change. Chicago: University of Chicago Press.

Calvin, William H. (1998) The Emergence of Intelligence, in Scientific American Presents 9 (4) 44-51, November 1998. < http://williamcalvin.com/1990s/1998SciAmer.htm >, retrieved 05 Oct 2005

Carey, Benedict (2007) "Denial Makes the World Go Round," NY Times < http://www.nytimes.com/2007/ll/20/health/research/20deni.html7pagewanted =all > retrieved 18 Feb 2008

Carr, Kim, The Hon. Senator, (2011) Minister for Innovation, Industry, Science and Research, Government of Australia. Personal conversation, Square Kilometer Array 2011 Forum dinner, The Banff Centre, Banff Alberta, 06 July

Carr, Nicholas (2008) The Big Switch: Rewiring the world, from Edison to Google. New York: W. Norton & Company

Carty, Arthur J. (2005a) Personal conversation, Privy Council Office, Government of Canada, Ottawa, Ontario, October 18

Carty, Arthur J. (2005b) PPT presentation, "Role of the National Science Advisor: Mandate, Challenges and Priorities", Celebrating Ingenuity. University of Calgary, 14 September 2004 (re-presented at the Privy Council Office, Government of Canada, Ottawa, Ontario, October 18)

Casti, John L. (1995) Complexification: Explaining a paradoxical world through the science of surprise. New York: Harper Perennial

Cetina, Karin Knorr (1999) Epistemic Cultures. How the Sciences Make Knowledge. Cambridge, MA: Harvard University Press

Christensen, Clayton M. (2003) The Innovator's Dilemma: The revolutionary book that will change the way you do business. New York: Harper

Christensen, Clayton M., Erik A. Roth and Scott D. Anthony (2004) Seeing What's Next: Using theories of innovation to predict industry change. Boston, MA: Harvard Business Press

Cilliers, Paul (2002). Why we cannot know complex things completely, Emergence, 4 (1/2), 77-84

Clemens, Samuel (1897) < http://www.twainquotes.com/Death.html >, retrieved 01 January 2011

211 Collingwood, R. G. (2002), Rex Martin (ed) An Essay on Metaphysics (Revised edition). New York: Oxford University Press

Collingwood, R. G. (1960) The Idea of Nature. New York: Oxford University Press

Collingwood, R. G. (1933) A Thesis on Philosophical Method. Oxford at the Clarendon Press

Corey, Elias James (1990) "The Logic of Chemical Synthesis: Multistep Synthesis of Complex Carbogenic Molecules", Nobel lecture < http://www.nobelprize.org/nobel_prizes/chemistry/laureates/1990/corey- lecture.pdf >, retrieved 24 Dec 2009

Davis, Stan and Christopher Myer (1999) Blur. The Speed of Change in the Connected Economy. New York: Warner Books

Dawkins, Richard (2006) The God Delusion. Boston, MA: Houghton Mifflin

Dawkins, Richard (1997) Climbing Mount Improbable. New York: W. W. Norton & Company

Dennett, Daniel (1996) Darwin's Dangerous Idea. Evolution and the meanings of life. New York: Touchstone

De Pree, Max (1993) Leadership Jazz. New York: Dell Publishing

Dill, Franz (2007) Keynote session at IBM's Alamden Institute, San Jose, California, April 11-13

Downey, Lorne and Robert A. Este (1984J curriculum outline, Education 520 (Educational Policy). Mimeo, 5pp. Division of Educational Administration, Faculty of Education, University of British Columbia

Downey, Lorne (1982) personal conversation, Centre for Policy Studies, Division of Higher Education and Educational Administration, Faculty of Education, The University of British Columbia.

Dyson, Esther (2002) Personal e-mail communication, February 01

Dyson, Freeman (2006) A Failure of Intelligence, MIT Technology Review. < http://www.technologyreview.com/computing/17724/ > Retrieved 19 March 2007

Eberhart, Russell C., and James Kennedy with Yuhui Shi (2001) Swarm Intelligence (The Morgan Kauffman Series in Evolutionary Computing) San Francisco: Morgan Kaufmann

212 Einstein, Albert (1905) On the Electrodynamics of Moving Bodies. < http://www.fourmilab.ch/etexts/einstein/specrel/specrel.pdf >, retrieved 15 January 2009

Eisner, Howard (2005) Managing Complex Systems. Thinking outside the box. Hoboken, NJ: John Wiley & Sons

Ellerson, Tessa (2009) "Dyson defends nuclear energy in interview," The Tufts Daily < http://www.tuftsdaily.com/dyson-defends-nuclear-energy-in-interview- 1.1936544#.TyLoD5gx2As > Retrieved 18 Aug 2010

Elmegreen, Bruce (2010) Presentation on High Performance Computing development implications for the growth and performance of the Square Kilometer Array, European Cooperation in Science and Technology (COST) strategic workshop on the non-science benefits of the SKA, Rome, Italy, 30 Mar

Elmegreen, Bruce (2010) Personal Conversation, Yorktown Heights, NY: IBM Thomas J. Watson Research Laboratories, 25 February

Este, Robert A. (2007) "The Necessity of Conceptual Skill Enhancement to Address Philosophical Challenges of New Science: Background and Implications", Invited Address. Cambridge, MA: New England Complex Systems Institute

Este, Robert A., and Stuart A. Kauffman (2005) Some Thoughts on Unprecedented Conceptual Challenges Presented by Holonic Multi-Agent Systems, proceedings of the 2005 IEEE International Conference on Systems, Man and Cybernetics, Waikaloa, Hawaii. October 10-12:1724-1729

Fagerberg, Jan, David C. Mowry and Ricard R. Nelson (eds) (2005) The Oxford handbook of innovation. New York: Oxford University Press

Feynman, Michelle (ed) (2005) Perfectly Reasonable Deviations from the Beaten Track. The Letters of Richard P. Feynman. Basic Books: New York

Feynman, Richard P. (1965) The Character of Physical Law. Cambridge, MA: MIT Press

Fogg, B. J. (1998) Persuasive computers: perspectives and research directions. Proceedings of the SIGCHI conference on Human factors in computing systems. New York: ACM Press / Addison - Wesley Publishing Co.

Fogg, B. J. (2002) Persuasive Technology: Using Computers to Change What We Think and Do (Interactive Technologies) Waltham, MA: Morgan Kaufmann

213 Frenken, Koen (2001) Understanding Product Innovation using Complex Systems Theory. Academic Thesis. Amsterdam: University of Amsterdam

Friedman, Milton (1990) Free to Choose. New York: Harcourt

Geertz, Clifford (1973) The Interpretation Of Cultures. New York: Basic Books

Gell-Mann, Murray (1995) The Quark and the Jaguar: Adventures in the Simple and the Complex. New York: St Martin's Griffin

Gettier, Edmund L. (1963) Is Justified True Belief Knowledge? Analysis, 23,121-123

Gleick, James (1999) Faster. The Acceleration of Just About Everything. New York: Pantheon Books Goebel, R. (2006) Personal conversation addressing the conceptual challenges of algorithm development and programming. Institute for Biocomplexity and Informatics, University of Calgary, February 19

Goldstein, Jeffrey (1999) Emergence as a Construct: History and Issues. Emergence, 1 (1), 49-72

Gervasi, V., & Prencipe, G. (2003) Coordination without communication: The case of the flocking problem. Unpublished paper. Pisa: University di Pisa, Dipartimento di Informatica. < http:// circe.di.unipi.it/~gervasi/Papers/dam02.pdf >, retrieved 11 Nov 2003

Ghiselin, Brewster (ed) (1952) The Creative Process. Scarborough, Ontario: The New American Library of Canada, Inc.

Gibson, William (1994) Interview segment in Visions of Heaven and Hell, VHS video series (170+ minutes, colour). London (UK): TVi Digital, Channel 4

Gould, Stephen Jay (2004) Henri Poincark The Value of Science; Essential Writings of Henri Poincare. New York: The Modern Library

Grinbaum, Alexei (2008) On the eve of the LHC: conceptual questions in high-energy physics, atXiv:0806vl [physics.soc-ph], retrieved 17 Nov 2009

Guba, Egon G., and Yvonna S. Lincoln (1981) Effective Evaluation: Improving the Usefulness of Evaluation Results Through Responsive and Naturalistic Approaches. San Francisco: Jossey-Bass

Hadamard, Jacques (1954) The Psychology of Invention in the Mathematical Field. New York: Dover Publications Inc.

214 Hall, Duncan (2009) SKA Technical and Engineering planning meeting, The University of Manchester, Manchester, UK, 23 Oct

Hall, N. (1991) Exploring chaos: A guide to the new science of disorder. New York: W. W. Norton

Handy, Charles (1996) Gods of Management: The Changing Work of Organizations. New York: Oxford University Press

Hanson, Norwood Russell (1970) Perception and discovery: An introduction to scientific inquiry. Beverly, MA: Wadsworth Lewin, Roger (1992) Complexity. Life at the edge of chaos. New York: Macmillan

Harman, Gilbert H (1965) The Inference to the Best Explanation, The Philosophical Review, Vol. 74, No. 1. (Jan.), pp. 88-95 < http://www.jstor.org/pss/2183532 >, retrieved 07 June 2008

Harris, Sam (2004) The End of Faith. Religion, terror, and the future of reason. New York: W. W. Norton and Company

Haslett, Jim and Leo Belestotski (2010) Discussion on low-noise amplifier specifications and design requirements for the Square Kilometer Array, during stopover in the Air Canada Lounge, Pierre Trudeau International Airport, Montreal, PQ, February 19

Haslett, Jim and Leo Belestotski. (2006) CMOS Ultra Low Noise LNAIC Designs for Radio Astronomy < http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.83.8289&rep=repl&type =pdf > retrieved 22 Oct 2009

Haslett, Jim (2009) Discussion on data rates and flows of the Square Kilometer Array, Institute for Space Imaging Science, The University of Calgary, Calgary, Alberta, 09 Dec

Hawking, S., and L. Mlodinow (2010) The Grand Design. Bantam: New York

Helft, Miguel (2011) The Class That Built Apps, and Fortunes. The New York Times < http://www.njrtimes.com/2011/05/08/technology/08class.html?partner=rss&emc =rss&pagewanted=all >, retrieved 15 June 2011

Herzfeld, Charles M. (1998) Technology for National Security: Report University of Michigan Library

Hesselbein, Frances, Marshall Goldsmith, and Iain Somerville (eds) (2002) Leading for Innovation and Organizing for Results. New York: Jossey-Bass

215 Hesselbein, Frances and Rob Johnson (2002) On Creativity, Innovation, and Renewal: A Leader to Leader Guide. New York: Wiley & Sons

Hildebrand, Alan (2009) Personal conversation on the topic of asteroid hunting using the Near Earth Object Surveillance Satellite (NEOSSat) being built at the University of Calgary, 13 Sept

Hofstadter, Douglas and Daniel Dennett (2001) The Mind's I: Fantasies and Reflections on Self & Soul. New York: Basic Books

Hofstadter, Douglas (1999) Godel, Escher, Bach: An Eternal Golden Braid. New York: Basic Books

Holland,J. (1992) Echoing emergence: Objectives, rough definitions, and speculations for echo-class models (# 93-04-023). Santa Fe, NM: Santa Fe Institute Working Papers, Preprints, and Reprints Series

Holland, John (1998) Emergence: From chaos to order. New York: Basic Books

Holland, John (1996) Hidden Order: How adaptation builds complexity. New York: Helix

Hillis, Danny (1999) Pattern on the Stone: The Simple Ideas That Make Computers Work. St. Louis, MO: San Val Inc

Holdren, John (2008) The Future of Climate Change Policy: The U.S.'s Last Chance to Lead. Scientific American, Earth 3.0 Supplement, October 13,20-21

Hyman, Sidney (1975) The Aspen Idea. Norman, OK: University of Oklahoma Press

Iansiti, Marco (1998) Technology Integration. Making critical choices in a dynamic world. Boston, MA: Harvard Business School Press

Jacobs, Christian (2001) Illustrated Evolutionary Computation with Mathematica. San Francisco: Morgan Kaufmann

Janis, Irving L. (1972) Victims of groupthink: A psychological study of foreign-policy decisions and fiascoes. Oxford, UK: Houghton Mifflin

Jen, Erica (ed) (2005) Robust Design. A repertoire of biological, ecological, and engineering case studies. New York: Oxford University Press

Johnson, Steven (2010) Where Good Ideas Come From: The natural history of innovation. New York: Riverhead Books

216 Kaern, Mads [Department of Physics, University of Ottawa, 150 Louis Pasteur, Ottawa, Ontario, K1N 6N5, Canada; Department of Cellular and Molecular Medicine and Ottawa Institute of Systems Biology, University of Ottawa, 451 Symth Road, Ottawa, Ontario, K1H8M5, Canada), speech at inaugural meeting of the Canadian Society for Systems Biology, Ottawa, Ontario, October, 2005

Kauffman, S. A. (2004) A proposal for using the ensemble approach to understand genetic regulatory networks./ Theor. Biol. 230,581-590

Kauffman, S.A. (1996) At Home in the Universe: The Search for the Laws of Self- Organization and Complexity, New York, Oxford University Press

Kauffman, S.A. (2000) Investigations, New York, Oxford University Press

Kauffman, Stuart A. (2005) Personal conversation addressing dynamic processes of innovation and opportunistic circumstances that permit assembly of parts to create a new whole, or to see opportunity for innovation in an original interpretation of form and function; steps leading to the creation of the Wright Flyer were described in great detail. Institute for Biocomplexity and Informatics, The University of Calgary. May 25

Kauffman, Stuart A. (2005) Personal conversation on the topic of "the inference problem" in the application of complex systems theory to evolving Systems Biology. The Institute for Biocomplexity and Informatics, The University of Calgary, Calgary, Alberta, March 22

Kauffman, Stuart A. (2008) Reinventing the Sacred: A New View of Science, Reason, and Religion. New York: Basic Books

Kauffman, S.A. (1993) The Origins of Order: Self-Organization and Selection in Evolution, New York: Oxford University Press.

Kauffman, Stuart A. (2000) United States Patent 6125351, "System and method for the synthesis of an economic web and the identification of market niches" < http://www.google.com/patents?hl=en&lr=&vid=USPAT612535l&id=OxMGAAAAE BAJ&oi=fhd&dq=%22Stuart+A.+Kaufftnan%22+%22Bios%22&printsec=abstract#v =onepage&q=%22Stuart%20A.%20Kauffman%22%20%22Bios%22&f=false >, originally discussed in private conversation with Stuart Kauffman January 2004; retrieved Sept 29 2009

Kauffman, Stuart, and Edward D. Weinberger, "The NK model of rugged fitness landscapes and its application to maturation of the immune response", Journal of Theoretical Biology, Vol 141, Issue 2, 21 Nov 1989, pp 211-245

217 Kauffman, S. A., Robert K. Logan, Robert Este, Randy Goebel, David Hobill and Ilya Shmulevich (2008) Propagating Organization: an inquiry, Biol Philos., 23:27-45; published online 20 March 2007

Kawasaki, Guy, and Michele Moreno (1999) Rules for revolutionaries: the capitalist manifesto for creating and marketing new products and services. New York: HarperBusiness

Kelley, Tom (2001) The Art of Innovation. New York: Doubleday

Kelly, George (1963) A Theory of Personality. The Psychology of Personal Constructs. New York: Norton

Kelly, Kevin (1998) New Rules for the New Economy. New York: Penguin

Koestler, Arthur (1968) The Ghost in the Machine. Basingstoke, Hampshire (UK): Macmillan

Kruglinski, S. When Even Mathematicians Don't Understand the Math, NYTimes < http://www.nytimes.com/2004/05/25/science/thesis-when-even- mathematicians-don-t-understand-the-math.html >, retrieved 14 June 2006

Kuhn, T. S. (1962) The Structure of Scientific Revolutions. Chicago: University of Chicago Press

Lakatos, Imre (1978) The Methodology of Scientific Research Programmes: Philosophical Papers Volume 1. Cambridge: Cambridge University Press

Lauden, L. (1977) Progress and its problems: towards a theory of scientific growth. London, UK: Routledge & Kegan Paul

Law etal (2009) "Route Designer: A Retrosynthetic Analysis Tool Utilizing Automated Retrosynthetic Rule Generation", J Chem Inf Model, 49 (3) 593-602

Lewin, Roger (1992) Complexity: life at the edge of chaos. Chicago: University of Chicago Press

Lindblom, Charles E. (1959) The Science of "Muddling Through". Public Administration Review, Vol. 19, No. 2 (Spring, 1959), pp. 79-88

Lissack, M. R. (1999) Complexity: The science, its vocabulary and its relation to organizations. Emergence,1 (1), 110-126

Loftus, Elizabeth F. (1996) Eyewitness Testimony. Cambridge, MA: Harvard University Press

218 Luft, J., and H. Ingham (1955) "The Johari window, a graphic model of interpersonal awareness". Proceedings of the western training laboratory in group development Los Angeles: UCLA

Machiavelli, Nicoli (1513; 1992) The Prince. New York: Dover Publications

Magnani, Lorenzo (2000) Abduction, Reason and Science. Processes of Discovery and Explanation. Dordrecht, The Netherlands: Springer

Magnani, Lorenzo & Nancy). Nersessian (eds) (2002) Model-Based Reasoning: Science, Technology, Values. New York: Kluwer/Plenum

McLuhan, Marshall (1964) Understanding Media. New York: McGraw-Hill

McCumber, John (2005) Reshaping Reason. Toward a new philosophy. Bloomington, IN: Indiana University Press

Mitchell, M. (1996) An Introduction to Genetic Algorithms, Cambridge, MA: MIT Press

Mokyr, J. (1999) The Gifts of Athena. Cambridge, MA: Princeton University Press

Morrison, D., Chapman, C. R., Steel, D., and Binzel R. P. (2004) "Impacts and the Public: Communicating the Nature of the Impact Hazard", in Mitigation of Hazardous Comets and Asteroids, (M.J.S. Belton, T.H. Morgan, N.H. Samarasinha and D.K. Yeomans, Eds), Cambridge, UK: Cambridge University Press

Murcho, Desidero (2006) Does science need philosophy? Revista Eletrdnica Informagao e Cognigao, v.5, n.2, p.50-58. Discussion Paper, Department of Philosophy, King's College London < http://www2.marilia.unesp.br/revistas/index.php/reic/article/viewFile/740/642 > retrieved Nov 08 2008

Murray, Charles (2003) Human Accomplishment: The Pursuit of Excellence in the Arts and Sciences, 800 B.C. to 1950. New York: Harper Collins

Nersessian, Nancy J. (1990) Faraday to Einstein: Constructing Meaning in Scientific Theories. Dordrecht, The Netherlands: Kluwer Academic Publishers

Nersessian, Nancy J. (1995) "Opening the Black Box: Cognitive Science and History of Science". Osiris, Constructing Knowledge in the History of Science 2nd Series, Vol. 10, pp. 194-211

Nicolis, G. and Prigogine, I. (1989) Exploring Complexity: an Introduction, New York: Freeman.

219 Nicholson, Peter (2009) Innovation and Business Strategy: Why Canada Falls Short. Ottawa, ON: Council of Canadian Academies

Nickles, Thomas (ed) (2002) Thomas Kuhn (Contemporary Philosophy in Focus). Cambridge, UK: Cambridge University Press

Nola, Robert, and Howard Sankey (2001) After Popper, Kuhn and Feyerabend: Recent Issues in Theories of Scientific Method. London, UK: Springer-Verlag London Ltd

Norman, Donald A. (2004) Emotional Design. Why we love (or hate) everyday things. New York: Basic Books

Norman, Donald A. (1993) Things that Make us Smart. Defending human attributes in the age of the machine. Cambridge, MA: Perseus Books

Papineau, David (ed) (1996) The Philosophy of Science. Oxford University Press: Oxford, UK

Peters, Tom (1987) Thriving on Chaos, New York: Harper & Row Publishers

Popper, Karl (2002) The Logic of Scientific Discovery (2nd ed). London, UK: Routledge

Peirce, C. S. (1934) 'Pragmatism and abduction', Collected Papers of Charles Sanders Peirce. Vol. IV: Pragmatism and Pragmaticism, C. Hartshorne & P. Weiss (eds.) Cambridge, MA: Harvard University Press

Postman, Neil (1994) Interview segment in Visions of Heaven and Hell, VHS video series (170+ minutes, colour). London (UK): TVi Digital, Channel 4

Pernu, T. K. (2008) Philosophy and the Front Line of Science, Q Rev Biol, 83 (1) 29- 36 Petersen, Alan, Alison Anderson & Stuart Allan (2005) Science fiction / science fact: medical genetics in news stories, New Genetics and Society, 24:3,337-353

Pollio, Howard (1974) Psychology of Symbolic Activity. New York: Addison-Wesley Educational Publishers Inc.

Prigogine, Ilya and Isabelle Stengers (1985) Order Out of Chaos: Man's new dialogue with nature. Waukegan, IL: Fontana Press

Pollack, J.B. (1991) The Induction of Dynamical Recognizers. Machine Learning, 7, 227-252

220 Quine, W. V. 0. (1969) 'Epistemology naturalized', Ontological Relativity and other Thesiss. New York: Columbia University Press

Rawls, J. (1971) A Theory of Justice. Cambridge, MA: Harvard University Press.

Ravetz, Jerome R. (2006) Scientific knowledge and its social problems. New Brunswick, NJ: Transaction Publishers

Reed, M. and Hughes, M. (eds) (1992) Rethinking Organization: New Directions in Organization Theory and Analysis. London: Sage

Ribeiro, Andr6, Rui Zhu and Stuart A. Kauffman (2006) Journal of Computational Biology. November, 13(9): 1630-1639. doi:10.1089/cmb.2006.13.1630.

Rittel, Horst W. J., and Melvin M. Webber (1973) Dilemmas in a General Theory of Planning, Policy Sciences 4 (2) pp 155-169

Rogers, Everett (1983) The Diffusion of Innovations (4th ed). New York: The Free Press

Rubinoff, Lionel (1970) Collingwood and the Reform of Metaphysics. A study in the philosophy of mind. Toronto: University of Toronto Press

Russell, Bertrand (1996) History of Western Philosophy. London, UK: Routledge Classics

Salam, Abdus (1990) Unifcation of Fundamental Forces: The first 1988 Dirac Memorial Lecture, "Einstein on Theory and Observation", pp 98-101. Cambridge, UK: Cambridge University Press

Sawyer, R. Keith (2006) Explaining Creativity. The Science of Human Innovation. New York: Oxford University Press

Schon, Donald A. (1983) The Reflective Practitioner. How Professional Think in Action. New York: Basic Books

Schon, Donald. (1967) Technology and change: the new Heraclitus, Oxford: Pergamon

Schwartz, Peter (1991) The Art of the Long View. New York: Doubleday Schumpeter, Joseph A. (2008) Capitalism, Socialism, and Democracy: Third Edition. New York: Harper Perennial Modern Classics

Schwarz, E. (2002). A systems holistic interpretation of the present state of contemporary society and its possible futures. Paper presented at the 5th European

221 Systems Science Congress, Heraklion, Crete, Oct. 16-19 2002 < http://www.afscet.asso.fr/resSystemica/Crete02/SchwarzB.pdf>, retrieved 21 Dec 2004

Searle, John R. (1999) The Future of Philosophy. Phil. Trans. R. Soc. Lond. 354,2069- 2080 London: The Royal Society

Shapin, Steven (2008) The Scientific Life. A moral history of a late modern vocation. University of Chicago Press: Chicago and London

Smolin, Lee (2010) Newtonian gravity in loop quantum gravity, arXic:1001.3668v2 [gr-qc] retrieved 22 Dec

Smolin, Lee (2006) The Trouble With Physics: The Rise of String Theory, The Fall of a Science, and What Comes Next. Boston, MA: Mariner Books

Strogatz, Steven H. (2004) Sync: The emerging science of spontaneous order. New York: Hyperion

Surowieki, James (2005) The Wisdom of Crowds. New York: Anchor

Syed, Naweed and Zhangxing (John) Chen (2009). Strategic discussion (including Russ Taylor) on data handling and analytics challenges in computational biology of neuronal modeling and brain imaging, petroleum reservoir modeling, and EVLA (Extended Very Large Array) data cube analysis addressing the problem of requiring exascale computing to meet the challenges of anticipated advanced research. The scale and scope of data handling and analytics challenges in the Square Kilometer Array (SKA) project are expected to far outstrip, and for many decades into the foreseeable future will continue to outstrip, any leading-edge scientific data challenges in any other research field. The implications are therefore that the SKA project is comprised of and will continue to advance innovation challenges and tool, equipment, powering, cooling, imaging and algorithm development requirements in the data handling and analytics fields that will inevitably and very strongly affect and lead all other fields of human endeavour for decades to come. Office of Naweed Syed, Faculty of Medicine, The University of Calgary, 24 Mar

Taylor, Russ (2009) Personal Conversation. Department of Physics and Astronomy / Institute for Space Imaging Science, The University of Calgary, Calgary, Alberta, 21 June

Tasaka, H. (1999) Twenty-first-century management and the complexity paradigm. Emergence, 1 (4), 115-123

Thagard, P. & Shelley, C. (1997) Abductive reasoning: Logic, visual thinking, and coherence. In: M.-L. Dalla Chiara et al (eds) Logic and Scientific methods. Dordrecht:

222 Kluwer, p.413-427; also available on-line at < http://c0gprints.0rg/671/l/FAbductive.html >, retrieved 18 April 2007

Thagard, Paul, and Jing Zhu (2001) Acupuncture, Incommensurability, and Conceptual Change. Discussion paper. Philosophy Department, The University of Waterloo < http://watarts.uwaterloo.ca/~pthagard/Articles/Pages/acupuncture.pdf>, retrieved 24 June 2006

Thompson, Clive (2003) PowerPoint Makes You Dumb. The New York Times Magazine < http://www.nytimes.eom/2003/12/14/magazine/2003-the-3rd- annual-year-in-ideas-powerpoint-makes-you-dumb.html > retrieved January 22 2004

Thompson, Clive (2009) "Your Outboard Brain Knows All", WIRED, 15.10 retrieved 16 Aug

Tichy, Noel M. (1983) Managing Strategic Change. Technical, political and cultural dynamics. New York: John Wiley & Sons

Torretti, Roberto (1999) The Philosophy of Physics. Cambridge, UK: Cambridge University Press

Tomsic, Astrid, and Daniel Suthers, (2006) Discussion Tool Effects on Collaborative Learning and Social Network Structure. Educational Technology & Society, 9 (4), 63- 77.

Tufte, Edward R. (1990) Envisioning Information. Cheshire, CT: Graphics Press

Tufte, Edward R. (2006) The Cognitive Style of PowerPoint: Pitching out corrupts within. Cheshire, CT: Graphics Press

Tufte, Edward R. (1983) The Visual Display of Quantitative Information. Cheshire, CT: Graphics Press

Tufte, Edward R. (1997) Visual Explanations. Images and Quantities, Evidence and Narrative. Cheshire, CT: Graphics Press

Tversky, Amos, and Daniel Kahneman (1974)Judgment under Uncertainty: Heuristics and Biases, Science, New Series, Vol. 185, No. 4157. (Sep. 27,1974), pp. 1124-1131< http://www.hss.caltech.edu/~camerer/Ecl01/JudgementUncertainty.pdf> retrieved 25 March 2007

Ulieru, Mihaela, and Robert A. Este (2004) The Holonic Enterprise and Theory Emergence: On emergent features of self-organization in distributed virtual agents,

223 International Journal Cybernetics and Human Knowing (Imprint Academic), Vol. 11, No. 1:79-99

Utterback, James M. (1994) Mastering the Dynamics of Innovation. Boston, MA: Harvard Business Press von Hippel, Eric (1988) The Sources of Innovation. New York: Oxford University Press von Oech, Roger (1992) A Whack on the Side of the Head. How you can be more creative. New York: Warner Books

Waldrop, Mitchell (1992) Complexity: the emerging science at the edge of order and chaos. New York: Simon and Schuster

Weick, Karl E. (1976) Educational Organizations as Loosely Coupled Systems. Administrative Science Quarterly, 21 (1), 1-19

Weinberg, Steven (1992) Dreams of a Final Theory. New York: Pantheon Books

Weisberg, Robert W. (2006) Creativity. Understanding Innovation in Problem Solving, Science, Invention, and the Arts. Hoboken, N.J.: John Wiley & Sons

Whitehead, Alfred North (1967) Science and the Modern World. New York: The Free Press

Whitehead, Alfred North, and Bertrand Russell (1905; 2010) Principia Mathematica Charleston, SC: Nabu Press

Wilkinson, P. N., K. I. Kellerman, R. D. Elkers, J. M. Cordes and T. J. W. Lazio (2004) The Exploration of the Unknown, New Astronomy Reviews, Science with the Square Kilometre Array, 48 (11-12), 1551-1563

Williamson, Timothy (2007) The Philosophy of Philosophy. Maiden, MA: Blackwell Publishing

Wilson, Thomas (no date) "The Arte of Rhetorique" < http://ebooks.gutenberg.us/Renascence_Editions/arte/arte2.htm >, retrieved 27 Sept 2010

Wimsat, William C. (2007) Re-Engineering Philosophy for Limited Beings: Piecewise Approximations to Reality. Cambridge, MA: Harvard University Press

Wolf, Gary "Steve Jobs: The Next Insanely Great Thing," WIRED, 4.02 < http://www.wired.eom/wired/archive/4.02/jobs_pr.html >, retrieved 22 July 2007

224 Wolfram, Stephen (2002) A New Kind of Science. Champaign, IL: Wolfram Media Inc.

Yin, Robert K. (2009) Case Study Research: Design and Methods (Applied Social Research Methods). New York: Sage Publications, Inc

Zeilinger, Anton "On the Interpretation and Philosophical Foundation of Quantum Mechanics", discussion paper, Institut fur Experiemtnalphysick, Universitat Wien, Austria. < http://www.quantum.at/fileadmin/zeilinger/philosoph.pdf>, retrieved 15 February 2006

225