The Creative Mind: Cognition, Society and Culture
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The Art and Science of Framing an Issue
MAPThe Art and Science of Framing an Issue Authors Contributing Editors © January 2008, Gay & Lesbian Alliance Against Defamation (GLAAD) and the Movement Advancement Project (MAP). All rights reserved. “Ideas are a medium of exchange and a mode of influence even more powerful than money, votes and guns. … Ideas are at the center of all political conflict.” —Deborah Stone, Policy Process Scholar, 2002 The Art and Science of 1 Framing an Issue an Issue and Science of Framing Art The The Battle Over Ideas 2 Understanding How People Think 2 What Is Framing? 4 Levels of Framing 5 Tying to Values 6 Why Should I Spend Resources on Framing? 6 How Do I Frame My Issue? 7 Step 1. Understand the Mindset of Your Target Audience 7 Step 2. Know When Your Current Frames Aren’t Working 7 Step 3. Know the Elements of a Frame 7 Step 4. Speak to People’s Core Values 9 Step 5. Avoid Using Opponents’ Frames, Even to Dispute Them 9 Step 6. Keep Your Tone Reasonable 10 Step 7. Avoid Partisan Cues 10 Step 8. Build a New Frame 10 Step 9. Stick With Your Message 11 “Ideas are a medium of exchange and a mode of influence even more powerful than money, votes and guns. … Ideas are at the center of all political conflict.” —Deborah Stone, Policy Process Scholar, 2002 2 The Battle Over Ideas Are we exploring for oil that’s desperately needed to drive our economy and sustain our nation? Or are we Think back to when you were 10 years old, staring at destroying delicate ecological systems and natural your dinner plate, empty except for a pile of soggy– lands that are a legacy to our grandchildren? These looking green vegetables. -
Lakoff's Theory of Moral Reasoning in Presidential Campaign
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Papers in Communication Studies Communication Studies, Department of 11-2013 Lakoff’s Theory of Moral Reasoning in Presidential Campaign Advertisements, 1952–2012 Damien S. Pfister University of Nebraska-Lincoln, [email protected] Jessy J. Ohl University of Mary Washington, [email protected] Marty Nader Nebraska Wesleyan University, [email protected] Dana Griffin Follow this and additional works at: http://digitalcommons.unl.edu/commstudiespapers Part of the American Politics Commons, and the Rhetoric Commons Pfister, Damien S.; Ohl, Jessy J.; Nader, Marty; and Griffin,a D na, "Lakoff’s Theory of Moral Reasoning in Presidential Campaign Advertisements, 1952–2012" (2013). Papers in Communication Studies. 53. http://digitalcommons.unl.edu/commstudiespapers/53 This Article is brought to you for free and open access by the Communication Studies, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Papers in Communication Studies by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. Published in Communication Studies 64:5 (November-December 2013; Special Issue: Consistency and Change in Political Campaign Communication: Ana- lyzing the 2012 Elections), pages 488-507; doi: 10.1080/10510974.2013.832340 Copyright © 2013 Central States Communication Association; published by Tay- digitalcommons.unl.edu lor & Francis Group. Used by permission. Published online October 18, 2013. Lakoff’s Theory of Moral Reasoning in Presidential Campaign Advertisements, 1952–2012 Jessy J. Ohl,1 Damien S. Pfister,1 Martin Nader,2 and Dana Griffin 1 Department of Communication Studies, University of Nebraska-Lincoln 2 Department of Political Science, University of Nebraska-Lincoln Corresponding author — Jessy J. -
A Framework for Representing Knowledge Marvin Minsky MIT-AI Laboratory Memo 306, June, 1974. Reprinted in the Psychology of Comp
A Framework for Representing Knowledge Marvin Minsky MIT-AI Laboratory Memo 306, June, 1974. Reprinted in The Psychology of Computer Vision, P. Winston (Ed.), McGraw-Hill, 1975. Shorter versions in J. Haugeland, Ed., Mind Design, MIT Press, 1981, and in Cognitive Science, Collins, Allan and Edward E. Smith (eds.) Morgan-Kaufmann, 1992 ISBN 55860-013-2] FRAMES It seems to me that the ingredients of most theories both in Artificial Intelligence and in Psychology have been on the whole too minute, local, and unstructured to account–either practically or phenomenologically–for the effectiveness of common-sense thought. The "chunks" of reasoning, language, memory, and "perception" ought to be larger and more structured; their factual and procedural contents must be more intimately connected in order to explain the apparent power and speed of mental activities. Similar feelings seem to be emerging in several centers working on theories of intelligence. They take one form in the proposal of Papert and myself (1972) to sub-structure knowledge into "micro-worlds"; another form in the "Problem-spaces" of Newell and Simon (1972); and yet another in new, large structures that theorists like Schank (1974), Abelson (1974), and Norman (1972) assign to linguistic objects. I see all these as moving away from the traditional attempts both by behavioristic psychologists and by logic-oriented students of Artificial Intelligence in trying to represent knowledge as collections of separate, simple fragments. I try here to bring together several of these issues by pretending to have a unified, coherent theory. The paper raises more questions than it answers, and I have tried to note the theory's deficiencies. -
George Lakoff and Mark Johnsen (2003) Metaphors We Live By
George Lakoff and Mark Johnsen (2003) Metaphors we live by. London: The university of Chicago press. Noter om layout: - Sidetall øverst - Et par figurer slettet - Referanser til slutt Innholdsfortegnelse i Word: George Lakoff and Mark Johnsen (2003) Metaphors we live by. London: The university of Chicago press. ......................................................................................................................1 Noter om layout:...................................................................................................................1 Innholdsfortegnelse i Word:.................................................................................................1 Contents................................................................................................................................4 Acknowledgments................................................................................................................6 1. Concepts We Live By .....................................................................................................8 2. The Systematicity of Metaphorical Concepts ...............................................................11 3. Metaphorical Systematicity: Highlighting and Hiding.................................................13 4. Orientational Metaphors.................................................................................................16 5. Metaphor and Cultural Coherence .................................................................................21 6 Ontological -
Conceptual Blending and Metaphor Theory 2.1
CHAPTER TWO CONCEPTUAL BLENDING AND METAPHOR THEORY 2.1 Metaphor Metaphor has fascinated and bothered philosophers since the ancient Greeks. Aristotle was the rst to de ne metaphor, and three compo- nents of his explanation have in uenced metaphorical analysis up to the twenty- rst century: the argument that metaphor is located at the level of word, rather than larger linguistic unit; his understanding of metaphor as deviant, non-literal word usage; and his belief that meta- phor is motivated by pre-existing similarity.1 Medieval commentators were chary of metaphor, seeing it primar- ily as a stylistic device. Metaphor may have been necessary in sacred discourse, because speaking of divine truths directly was impossible. But metaphor outside of sacred texts was dangerous. Later empiricist and rationalist philosophies also believed metaphor to be deceptive; literal language was the only satisfactory way to assert truth claims or to speak accurately. For them, metaphor undermined correct reasoning and should be avoided. As John Locke said, . [I]f we would speak of things as they are, we must allow that . all the arti cial and gurative application of words eloquence hath invented, are for nothing else but to insinuate wrong ideas, move the passions, and thereby mislead the judgment; and so indeed are perfect cheats. and where truth and knowledge are concerned, cannot but be thought a great fault, either of the language or person that makes use of them.2 Early twentieth century philosophy distinguished between language’s “cognitive” and “emotive” purposes; scienti c knowledge could be stated literally, and its truth veri\ ed independently. -
The Democratization of Artificial Intelligence
Metaphors We Live By1 Three Commentaries on Artificial Intelligence and the Human Condition Anne Dippel Prelude In the following essay, I want to bring together three stand-alone commentaries, each dealing with a different facet of artificial intelligence, and each revolving around a different underlying metaphor: intelligence, evolution, and play. The first commentary constitutes an auto-ethnographic vignette, which provides a framework for the reflection on artificial “intelligence” and the alleged capacity of machines to “think”; both very problematic metaphors from the feminist per- spective on (predominantly) female labour of bearing and rearing intelligent hu- man beings. The second one is an insight into my current ethnographic fieldwork amongst high-energy physicists who use machine-learning methods in their daily work and succumb to a Darwinist metaphor in imagining the significance of evo- lutionary algorithms for the future of humanity. The third commentary looks into “playing” algorithms and brings into the conversation the much-debated anthro- pological category of an “alien” which, as I argue, is much more relevant in order to understand AI than a direct personification, bringing a non-human entity to life. A New Non-artificial Intelligent Life is Born I am looking at a newly born human being. Day by day I keep him company, as he practices increasingly complex bodily movements, senses the inner emotions of other bodies around him or reacts to a sea of indistinguishable voices, despite not being able to understand the meaning of a single word. While he keeps to his 1 The title of a famous book published by George Lakoff and Mark Johnson in 1980. -
An Interview with George Lakoff
An Inrerview with George Lakoff An Interview with George Lakoff FRANCISCO JOSÉ RUIZ DE MENDOZA IBÁÑEZ Universidad de La Rioja CICigüeña, 60 Logroño - 26004 BIOGRAPHICAL NOTE George Lakoff teaches linguistics and cognitive science at the University of Califomia, Berkeley. Together with such figures as James McCawley, Paul Postal, and Haj Ross, he was one of the founders of the Generative Semantics movement in the 1960's. This represented the earliest major depamre from the standard Chomskyan Generative Transformational Grammar by demonstrating the fundamental role played by semantics and pragmatics in grammar. Since the mid-1970's Lakoff has become a leading figure in the development of Cognitive Liistics, which grounds linguistic theory in empirical findings from the field of Cognitive Psychology . He has studied conceptual systems in depth, although the bulk of his most recent research has increasingly focused on metaphor and its consequences for abstract reasoning. He is the author of Women, Fire, and Dangerous Things, and co-author of Metaphors We Live By (with Mark Johnson), and More Than Cool Reason (with Mark Turner). His most recent book, Moral Politics: What Conservatives Know That Liberals Don't, analyses the language of political discourse and demonstrates that conservative and liberal ideas are based on opposite metaphorical models of the family and morality. At present, he is writing Philosophy in the Flesh, in collaboration with Mark Johnson, which interprets philosophy from the point of view of cognitive science. He is also working, with Rafael Núiíez, on the metaphorical stnicture of mathematics. INTERVIEW' Good afternoon, Professor Lakoff. First of all, I'd like to go back to rhe late 1960's and early 1970's. -
Metaphor: a Computational Perspective
Strapparava, Carlo. 2018. Book Reviews. Computational Linguistics, uncorrected proof. Metaphor: A Computational Perspective Tony Veale, Ekaterina Shutova, and Beata Beigman Klebanov (University College Dublin, University of Cambridge, Educational Testing Service) Morgan & Claypool (Synthesis Lectures on Human Language Technologies, edited by Graeme Hirst, volume 31), 2016, xi+148 pp; paperback, ISBN 9781627058506, $55.00; ebook, ISBN 9781627058513; doi:10.2200/S00694ED1V01Y201601HLT031 Reviewed by Carlo Strapparava FBK-irst Metaphors are intriguing. We know that George Lakoff and Mark Johnson, in their book Metaphors We Live By, pointed out that our daily language is full of metaphors (Lakoff and Johnson 1980). Metaphors are not rare at all as linguistic events and in general as a means of human communication (e.g., in visual art). Thus, more than an exception, they seem to be a necessity for our mind. People use metaphors as strategies to link concepts, to deal with situations, and sometimes to suggest solutions to problems. For example, you can see criminality as a monster or as an illness. What you have in mind to deal with it is probably to fight in the former case, and to cure or to plan prevention in the latter. Nonetheless, metaphors are extremely difficult to model in a computational framework. What is literal? What is metaphorical? Making this distinction has often proved to be a daunting task, even for a human judgment. Metaphors—so bound to our way of thinking and entangled with a huge quantity of knowledge and linguistics subtleties— constitute an excellent research problem for computational linguistics and artificial intelligence in general. We could probably say that they belong to the AI-complete problems. -
Mccarthy As Scientist and Engineer, with Personal Recollections
Articles McCarthy as Scientist and Engineer, with Personal Recollections Edward Feigenbaum n John McCarthy, professor emeritus of com - n the late 1950s and early 1960s, there were very few people puter science at Stanford University, died on actually doing AI research — mostly the handful of founders October 24, 2011. McCarthy, a past president (John McCarthy, Marvin Minsky, and Oliver Selfridge in of AAAI and an AAAI Fellow, helped design the I Boston, Allen Newell and Herbert Simon in Pittsburgh) plus foundation of today’s internet-based computing their students, and that included me. Everyone knew everyone and is widely credited with coining the term, artificial intelligence. This remembrance by else, and saw them at the few conference panels that were held. Edward Feigenbaum, also a past president of At one of those conferences, I met John. We renewed contact AAAI and a professor emeritus of computer sci - upon his rearrival at Stanford, and that was to have major con - ence at Stanford University, was delivered at the sequences for my professional life. I was a faculty member at the celebration of John McCarthy’s accomplish - University of California, Berkeley, teaching the first AI courses ments, held at Stanford on 25 March 2012. at that university, and John was doing the same at Stanford. As – AI Magazine Stanford moved toward a computer science department under the leadership of George Forsythe, John suggested to George, and then supported, the idea of hiring me into the founding fac - ulty of the department. Since we were both Advanced Research Project Agency (ARPA) contract awardees, we quickly formed a close bond concerning ARPA-sponsored AI research and gradu - ate student teaching. -
Arxiv:2106.11534V1 [Cs.DL] 22 Jun 2021 2 Nanjing University of Science and Technology, Nanjing, China 3 University of Southampton, Southampton, U.K
Noname manuscript No. (will be inserted by the editor) Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact Yinyu Jin1 · Sha Yuan1∗ · Zhou Shao2, 4 · Wendy Hall3 · Jie Tang4 Received: date / Accepted: date Abstract The Turing Award is recognized as the most influential and presti- gious award in the field of computer science(CS). With the rise of the science of science (SciSci), a large amount of bibliographic data has been analyzed in an attempt to understand the hidden mechanism of scientific evolution. These include the analysis of the Nobel Prize, including physics, chemistry, medicine, etc. In this article, we extract and analyze the data of 72 Turing Award lau- reates from the complete bibliographic data, fill the gap in the lack of Turing Award analysis, and discover the development characteristics of computer sci- ence as an independent discipline. First, we show most Turing Award laureates have long-term and high-quality educational backgrounds, and more than 61% of them have a degree in mathematics, which indicates that mathematics has played a significant role in the development of computer science. Secondly, the data shows that not all scholars have high productivity and high h-index; that is, the number of publications and h-index is not the leading indicator for evaluating the Turing Award. Third, the average age of awardees has increased from 40 to around 70 in recent years. This may be because new breakthroughs take longer, and some new technologies need time to prove their influence. Besides, we have also found that in the past ten years, international collabo- ration has experienced explosive growth, showing a new paradigm in the form of collaboration. -
WHY PEOPLE THINK COMPUTERS CAN't Marvin
WHY PEOPLE THINK COMPUTERS CAN'T Marvin Minsky, MIT First published in AI Magazine, vol. 3 no. 4, Fall 1982. Reprinted in Technology Review, Nov/Dec 1983, and in The Computer Culture, (Donnelly, Ed.) Associated Univ. Presses, Cranbury NJ, 1985 Most people think computers will never be able to think. That is, really think. Not now or ever. To be sure, most people also agree that computers can do many things that a person would have to be thinking to do. Then how could a machine seem to think but not actually think? Well, setting aside the question of what thinking actually is, I think that most of us would answer that by saying that in these cases, what the computer is doing is merely a superficial imitation of human intelligence. It has been designed to obey certain simple commands, and then it has been provided with programs composed of those commands. Because of this, the computer has to obey those commands, but without any idea of what's happening. Indeed, when computers first appeared, most of their designers intended them for nothing only to do huge, mindless computations. That's why the things were called "computers". Yet even then, a few pioneers -- especially Alan Turing -- envisioned what's now called "Artificial Intelligence" - or "AI". They saw that computers might possibly go beyond arithmetic, and maybe imitate the processes that go on inside human brains. Today, with robots everywhere in industry and movie films, most people think Al has gone much further than it has. Yet still, "computer experts" say machines will never really think. -
The Qualia Manifesto (C) Ken Mogi 1998 [email protected] the Qualia Manifesto Summar
The Qualia Manifesto (c) Ken Mogi 1998 [email protected] http://www.qualia-manifesto.com The Qualia Manifesto Summary It is the greatest intellectual challenge for humanity at present to elucidate the first principles behind the fact that there is such a thing as a subjectiveexperience. The hallmark of our subjective experiences is qualia. It is the challenge to find the natural law behind the neural generation of qualia which constitute the percepts in our mind, or to go beyond the metaphor of a "correspondence" between physical and mental processes. This challenge is necessary to go beyond the present paradigm of natural sciences which is based on the so-called objective point of view of description. In order to pin down the origin of qualia, we need to incorporate the subjective point of view in a non-trivial manner. The clarification of the nature of the way how qualia in our mind are invoked by the physical processes in the brain and how the "subjectivity" structure which supports qualia is originated is an essential step in making compatible the subjective and objective points of view. The elucidation of the origin of qualia rich subjectivity is important not only as an activity in the natural sciences, but also as a foundation and the ultimate justification of the whole world of the liberal arts. Bridging the gap between the two cultures (C.P.Snow) is made possible only through a clear understanding of the origin of qualia and subjectivity. Qualia symbolize the essential intellectual challenge for the humanity in the future.