Society As a Complex Adaptive System
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What Is a Complex Adaptive System?
PROJECT GUTS What is a Complex Adaptive System? Introduction During the last three decades a leap has been made from the application of computing to help scientists ‘do’ science to the integration of computer science concepts, tools and theorems into the very fabric of science. The modeling of complex adaptive systems (CAS) is an example of such an integration of computer science into the very fabric of science; models of complex systems are used to understand, predict and prevent the most daunting problems we face today; issues such as climate change, loss of biodiversity, energy consumption and virulent disease affect us all. The study of complex adaptive systems, has come to be seen as a scientific frontier, and an increasing ability to interact systematically with highly complex systems that transcend separate disciplines will have a profound affect on future science, engineering and industry as well as in the management of our planet’s resources (Emmott et al., 2006). The name itself, “complex adaptive systems” conjures up images of complicated ideas that might be too difficult for a novice to understand. Instead, the study of CAS does exactly the opposite; it creates a unified method of studying disparate systems that elucidates the processes by which they operate. A complex system is simply a system in which many independent elements or agents interact, leading to emergent outcomes that are often difficult (or impossible) to predict simply by looking at the individual interactions. The “complex” part of CAS refers in fact to the vast interconnectedness of these systems. Using the principles of CAS to study these topics as related disciplines that can be better understood through the application of models, rather than a disparate collection of facts can strengthen learners’ understanding of these topics and prepare them to understand other systems by applying similar methods of analysis (Emmott et al., 2006). -
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Advances in Social Science, Education and Humanities Research, volume 124 International Conference on Contemporary Education, Social Sciences and Humanities (ICCESSH 2017) Information Ecology in Structuring Sociocultural Space of Modern Society Eleonora Barkova Department of History and Philosophy Plekhanov Russian University of Economics (PRUE) Stremyanny per., 36, Moscow, 117997, Russia E-mail: [email protected] Marina Ivleva Elena Agibalova Department of History and Philosophy Department of Foreign Languages № 3 Plekhanov Russian University of Economics (PRUE) Plekhanov Russian University of Economics (PRUE) Stremyanny per., 36, Moscow, 117997, Russia Stremyanny per., 36, Moscow, 117997, Russia Abstract—The article studies potential application of an living, for the ecosystem on all the levels were also identified. information ecology approach for the analysis of a V.A.Kutyrev was right to say that today “it’s important…to contemporary stage in the development of an information suggest some sort of a modus vivendi between realism and society. It is illustrated using the example of this approach modernism that reflects our natural, objective macro world utilized to study a social element – sociocultural space. The and post-modernism as, actually, the ideology of other, article analyses distinctive features of information ecology as a informative-virtual micro and mega worlds. Ecological modern philosophical approach based on holistic and problems that had been referred to nature not long ago, systematic principles which provides -
Adaptive Capacity and Traps
Copyright © 2008 by the author(s). Published here under license by the Resilience Alliance. Carpenter, S. R., and W. A. Brock. 2008. Adaptive capacity and traps. Ecology and Society 13(2): 40. [online] URL: http://www.ecologyandsociety.org/vol13/iss2/art40/ Insight Adaptive Capacity and Traps Stephen R. Carpenter 1 and William A. Brock 1 ABSTRACT. Adaptive capacity is the ability of a living system, such as a social–ecological system, to adjust responses to changing internal demands and external drivers. Although adaptive capacity is a frequent topic of study in the resilience literature, there are few formal models. This paper introduces such a model and uses it to explore adaptive capacity by contrast with the opposite condition, or traps. In a social– ecological rigidity trap, strong self-reinforcing controls prevent the flexibility needed for adaptation. In the model, too much control erodes adaptive capacity and thereby increases the risk of catastrophic breakdown. In a social–ecological poverty trap, loose connections prevent the mobilization of ideas and resources to solve problems. In the model, too little control impedes the focus needed for adaptation. Fluctuations of internal demand or external shocks generate pulses of adaptive capacity, which may gain traction and pull the system out of the poverty trap. The model suggests some general properties of traps in social–ecological systems. It is general and flexible, so it can be used as a building block in more specific and detailed models of adaptive capacity for a particular region. Key Words: adaptation; allostasis; model; poverty trap; resilience; rigidity trap; transformation INTRODUCTION it seems empty of ideas, it will be abandoned or transformed into something else. -
A Complex Adaptive Systems Perspective to Appreciative Inquiry: a Theoretical Analysis Payam Saadat George Fox University
http://journals.sfu.ca/abr ADVANCES IN BUSINESS RESEARCH 2015, Volume 6, pages 1-13 A Complex Adaptive Systems Perspective to Appreciative Inquiry: A Theoretical Analysis Payam Saadat George Fox University Appreciate inquiry is utilized to facilitate organizational change by encouraging stakeholders to explore positives and generative capacities within their organization. In the literature, analysis of the effectiveness of AI is confined to psychological and managerial explanations such as highlighting the promotion of positive mindset and collective organizational planning. This paper will discuss a complex adaptive systems (CAS) perspective and present a new model for understanding the functionality of AI. The emphasis of this paper is placed on exploring the effects of AI on the behavior and interactions of agents/employees related to how they cope with change. An analysis of AI’s functionality through the lens of CAS reveals two critical insights: a) AI enhances adaptability to change by strengthening communication among agents, which in turn fosters the emergence of effective team arrangements and a more rapid collective response to change and b) AI possesses the potential to generate a collective memory for social systems within an organization. Furthermore, a systematic analysis of AI indicates a close connection between this method and CAS-based styles of management. This paper concludes by suggesting that AI might represent a potential method with the capacity to place organizational teams at the edge of chaos. Keywords: appreciative inquiry, organizational change, management, complex adaptive systems, edge of chaos Introduction In today’s fast-paced world where the fluctuating preferences of consumers, the growth in the global web of interdependence, and technological advancements guide the co-evolving relationship between the dominant business environment and the social systems within its domain, an organization’s capacity to cope with change in a timely manner determines its survival (Hesselbein & Goldsmith, 2006; Macready & Meyer, 1999; Senge, 2006). -
The Effects of Feedback Interventions on Performance: a Historical Review, a Meta-Analysis, and a Preliminary Feedback Intervention Theory
Psychological Bulletin Copyright 1996 by the American Psychological Association, Inc. 1996, Vol. II9, No. 2, 254-284 0033-2909/96/S3.00 The Effects of Feedback Interventions on Performance: A Historical Review, a Meta-Analysis, and a Preliminary Feedback Intervention Theory Avraham N. Kluger Angelo DeNisi The Hebrew University of Jerusalem Rutgers University Since the beginning of the century, feedback interventions (FIs) produced negative—but largely ignored—effects on performance. A meta-analysis (607 effect sizes; 23,663 observations) suggests that FIs improved performance on average (d = .41) but that over '/3 of the FIs decreased perfor- mance. This finding cannot be explained by sampling error, feedback sign, or existing theories. The authors proposed a preliminary FI theory (FIT) and tested it with moderator analyses. The central assumption of FIT is that FIs change the locus of attention among 3 general and hierarchically organized levels of control: task learning, task motivation, and meta-tasks (including self-related) processes. The results suggest that FI effectiveness decreases as attention moves up the hierarchy closer to the self and away from the task. These findings are further moderated by task characteristics that are still poorly understood. To relate feedback directly to behavior is very confusing. Results able has been historically disregarded by most FI researchers. This are contradictory and seldom straight-forward. (Ilgen, Fisher, & disregard has led to a widely shared assumption that FIs consis- Taylor, 1979, p. 368) tently improve performance. Fortunately, several FI researchers The effects of manipulation of KR [knowledge of results] on motor (see epigraphs) have recently recognized that FIs have highly vari- learning. -
Systems That Adapt to Their Users
Systems That Adapt to Their Users Anthony Jameson and Krzysztof Z. Gajos DFKI, German Research Center for Artificial Intelligence Harvard School of Engineering and Applied Sciences Introduction This chapter covers a broad range of interactive systems which have one idea in common: that it can be worthwhile for a system to learn something about individual users and adapt its behavior to them in some nontrivial way. A representative example is shown in Figure 20.1: the COMMUNITYCOMMANDS recommender plug-in for AUTO- CAD (introduced by Matejka, Li, Grossman, & Fitzmau- rice, 2009, and discussed more extensively by Li, Mate- jka, Grossman, Konstan, & Fitzmaurice, 2011). To help users deal with the hundreds of commands that AUTO- CAD offers—of which most users know only a few dozen— COMMUNITYCOMMANDS (a) gives the user easy access to several recently used commands, which the user may want to invoke again soon; and (b) more proactively suggests com- mands that this user has not yet used but may find useful, Figure 20.1: Screenshot showing how COMMUNITY- given the type of work they have been doing recently. COMMANDS recommends commands to a user. (Image supplied by Justin Matejka. The length of the darker bar for a com- Concepts mand reflects its estimated relevance to the user’s activities. When the user A key idea embodied in COMMUNITYCOMMANDS and the hovers over a command in this interface, a tooltip appears that explains the command and might show usage hints provided by colleagues. See also other systems discussed in this chapter is that of adapta- http://www.autodesk.com/research.) tion to the individual user. -
Complexity of Social Systems and Paradoxes of Contemporary Security Theory and Policy Making
Czeslaw Mesjasz Cracow University of Economics Kraków, Poland [email protected] Complexity of social systems and paradoxes of contemporary security theory and policy making Paper presented at the CEEISA-ISA 2016 Joint International Conference Ljubljana, Slovenia 23-25 June 2016 (A very preliminary crude draft version, not for quotation) 1. Introduction The grand ideas such as, for example, the risk society of Beck [1992], complexity-stimulated crises discussed by Tainter [1988, 2000], Diamond [1997, 2005], ingenuity gap of Homer-Dixon [2002], and other similar, less publicized visions, lead to the following question. Was the world simpler and less risky in the past? The question brings about several paradoxes embodying actors and issues relating to broadly defined security. On the one hand we are intuitively aware that the present global society with development of IT and all its consequences, increasing number of societal interactions and environmental threats is becoming more difficult to comprehend. On the other, modern science allows for better understanding of the world. It may be then hypothesize that the contemporary discourse on the risk society and complexity of society is not correct when compared with the state of the world in any time in the past and much lower level of understanding of the world in that time. It may be even stated provocatively that although the number of social scientists is increasing only a relatively small of them have a deepened knowledge about the modern social proceses. The above paradox is used as a point of departure of the study of the links between complexity of society in the past and at present, and occurrence of large scale socioeconomic crises (countries, regions, continents, global scale). -
An Analysis of Power and Stress Using Cybernetic Epistemology Randall Robert Lyle Iowa State University
Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations 1992 An analysis of power and stress using cybernetic epistemology Randall Robert Lyle Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/rtd Part of the Educational Psychology Commons, Family, Life Course, and Society Commons, and the Philosophy Commons Recommended Citation Lyle, Randall Robert, "An analysis of power and stress using cybernetic epistemology " (1992). Retrospective Theses and Dissertations. 10131. https://lib.dr.iastate.edu/rtd/10131 This Dissertation is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Retrospective Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer. The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely afreet reproduction. In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand corner and continuing from lefr to right in equal sections with small overlaps. -
Chapter 17: Social Change and Collective Behavior
CHAPTER 17 SocialSocial ChangeChange andand CollectiveCollective BehaviorBehavior 566 U S Your Sections I Sociological N Imagination 1. Social Change G 2. Theoretical Perspectives on Social Change hen you see photos or films showing the Plains Indians of the 3. Collective Behavior WOld West—Sioux, Crow, and so forth—what do you think about the culture 4. Social Movements of those Native Americans? If you’re like most of us, you may assume that it had re- mained unchanged for many centuries—that these people dressed and acted in exactly Learning Objectives the same way as their ancestors. We often assume that nonindustrial soci- eties such as these stand still over time. After reading this chapter, you will be able to Actually, though, sociology teaches us that change comes to all societies. Whether by ❖ illustrate the three social processes that borrowing from other cultures, discovering contribute to social change. new ways of doing things, or creating inven- ❖ discuss how technology, population, nat- tions that ripple through society, all peoples ural environment, revolution, and war experience social change. cause cultures to change. Let’s return to the example of the Plains Indians. You may picture these tribes as ❖ describe social change as viewed by the fierce, buffalo-hunting warriors. Perhaps im- functionalist and conflict perspectives. ages of Sitting Bull and Crazy Horse astride ❖ discuss rumors, fads, and fashions. fast horses attacking Custer come to mind, ❖ compare and contrast theories of crowd leading you to think that their ancestors for centuries had also ridden horses. In fact, behavior. horses were a relatively recent introduction ❖ compare and contrast theories of social to Plains Indian culture in the 1800s. -
Collective Behaviour
COLLECTIVE BEHAVIOUR DEFINED COLLECTIVE BEHAVIOUR • The term "collective behavior" was first used by Robert E. Park, and employed definitively by Herbert Blumer, to refer to social processes and events which do not reflect existing social structure (laws, conventions, and institutions), but which emerge in a "spontaneous" way. Collective Behaviour defined • Collective behaviour is a meaning- creating social process in which new norms of behaviour that challenges conventional social action emerges. Examples of Collective Behaviour • Some examples of this type of behaviour include panics, crazes, hostile outbursts and social movements • Fads like hula hoop; crazes like Beatlemania; hostile outbursts like anti- war demonstrations; and Social Movements. • Some argue social movements are more sophisticated forms of collective behaviour SOCIAL MOVEMENTS • Social movements are a type of group action. They are large informal groupings of individuals and/or organizations focused on specific political or social issues, in other words, on carrying out, resisting or undoing a social change. CBs and SMs 19th C. ROOTS • Modern Western social movements became possible through education and the increased mobility of labour due to the industrialisation and urbanisation of 19th century societies Tilly’s DEFINITION SM • Charles Tilly defines social movements as a series of contentious performances, displays and campaigns by which ordinary people made collective claims on others [Tilly, 2004].]: Three major elements of SMs • For Tilly, social movements are a major vehicle for ordinary people's participation in public politics [Tilly, 2004:3]. • He argues that there are three major elements to a social movement [Tilly, 2004 THREE ELEMENTS OF SMs 1. Campaigns: a sustained, organized public effort making collective claims on target authorities; 2. -
An Accidental Resource: the Social Ecological System Framework Applied to Small Wetlands in Sierran Foothill Oak Woodlands1
An Accidental Resource: the Social Ecological System Framework Applied to Small Wetlands in Sierran Foothill Oak 1 Woodlands 2 2 3 Tracy V. Hruska, Lynn Huntsinger, and Jose L. Oviedo, Abstract An ongoing study of the small wetlands in the northern Sierra Nevada foothill oak woodlands that provide habitat for the state-threatened California black rail (Laterallus jamaicensis coturniculus) offers an example of the way that the social ecological systems (SES) framework can be used to analyze a natural resource problem. At the outset, it was hypothesized that the area’s hydrology, West Nile Virus from wetland mosquitos, the population ecology of the bird, and the decisions of landowners would have important impacts on the wetlands and birds. A SES framework was applied to identify and understand the interactions among ecological and human factors. The case of irrigated wetlands in Sierra foothill woodlands turns out to be an example of a fractured SES. Actions within the social system are having profound impacts on the natural system, but these resulting changes in the natural system appear to have little or no feedback to the social system. Intervention points identified include education of landowners, influencing water districts, and incentivizing conservation. Key words: California black rail, irrigation, pasture, water conservation, wildlife Introduction: social ecological systems Small wetlands in the northern Sierra Nevada foothill oak woodlands provide habitat for the state-threatened California black rail (Laterallus jamaicensis coturniculus). One ongoing study of the sustainability of the wetlands offers an example of the way that the social ecological systems (SES) framework can be used to analyze a natural resource problem. -
Systems Theory
1 Systems Theory BRUCE D. FRIEDMAN AND KAREN NEUMAN ALLEN iopsychosocial assessment and the develop - nature of the clinical enterprise, others have chal - Bment of appropriate intervention strategies for lenged the suitability of systems theory as an orga - a particular client require consideration of the indi - nizing framework for clinical practice (Fook, Ryan, vidual in relation to a larger social context. To & Hawkins, 1997; Wakefield, 1996a, 1996b). accomplish this, we use principles and concepts The term system emerged from Émile Durkheim’s derived from systems theory. Systems theory is a early study of social systems (Robbins, Chatterjee, way of elaborating increasingly complex systems & Canda, 2006), as well as from the work of across a continuum that encompasses the person-in- Talcott Parsons. However, within social work, sys - environment (Anderson, Carter, & Lowe, 1999). tems thinking has been more heavily influenced by Systems theory also enables us to understand the the work of the biologist Ludwig von Bertalanffy components and dynamics of client systems in order and later adaptations by the social psychologist Uri to interpret problems and develop balanced inter - Bronfenbrenner, who examined human biological vention strategies, with the goal of enhancing the systems within an ecological environment. With “goodness of fit” between individuals and their its roots in von Bertalanffy’s systems theory and environments. Systems theory does not specify par - Bronfenbrenner’s ecological environment, the ticular theoretical frameworks for understanding ecosys tems perspective provides a framework that problems, and it does not direct the social worker to permits users to draw on theories from different dis - specific intervention strategies.