Managing Complex Adaptive Social Systems

Author(s):  
Roy Williams

Complex Adaptive Systems, for our purposes, are social systems that that evolve and display new, emergent properties, and self-organizing behavior of their components; they are based on a reasonably stable infrastructure, on the satisfaction of the most basic needs, and flexible, frequent, and open communication and interaction. Complex Adaptive Systems may be based on a few, simple rules, but can yield complex and unpredictable outcomes. The ‘Hole in the Wall’ project is an interesting case in point in the design of spaces for complex adaptive systems, or complex adaptive networks. In this project, touch screen computers were literally put in ‘holes in walls’ in places where unschooled children congregated. The children were given no instructions on how to use the computers, or what to do with them, but with startling results: the children soon taught themselves how to use the computers and the Internet, and much more (Mitra, 2003).


Systems ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 7
Author(s):  
John Turner ◽  
Dave Snowden ◽  
Nigel Thurlow

The substrate-independence theory utilizes sensemaking techniques to provide cognitively based scaffolds that guide and structure learning. Scaffolds are cognitive abstractions of constraints that relate to information within a system. The substrate-independence theory concentrates on the flow of information as the underlying property of the host system. The substrate-independence theory views social systems as complex adaptive systems capable of repurposing their structure to combat external threats by utilizing constructors and substrates. Constructor theory is used to identify potential construction tasks, the legitimate input and output states that are possible, to map the desired change in the substrate’s attributes. Construction tasks can be mapped in advance for ordered and known environments. Construction tasks may also be mapped in either real-time or post hoc for unordered and complex environments using current sensemaking techniques. Mapping of the construction tasks in real-time becomes part of the landscape, and scaffolds are implemented to aid in achieving the desired state or move to a more manageable environment (e.g., from complex to complicated).



2018 ◽  
Vol 11 (1) ◽  
pp. 70-90 ◽  
Author(s):  
Enrique Rubio Royo ◽  
Susan Cranfield McKay ◽  
Jose Carlos Nelson-Santana ◽  
Ramiro N Delgado Rodríguez ◽  
Antonio A. Ocon-Carreras

This article describes a proposal for sustainable way to adapt to current complex process of global transformation, using the ‘Web Knowledge Turbine' (WKT) as a self-organised ecosystem for the co-creation of personal and collective narratives. The authors contemplate all human social systems as Complex Adaptive Systems with the capacity for self-organisation derived from a permanent learning process. Accordingly, a shift in the focus of teaching programmes from mere mechanisms of knowledge transmission, to a process focused on learning and in particular, a process of self-directed, connected, and deep learning which has at its core the profile of the eLearner as the central protagonist. The cornerstone of this process is a Complex Ecosystem of Personal Knowledge (CEPK) which will support teaching at an undergraduate level, progressively and transversely, from its outset. Considering the classroom as a networked community of learners whose objective is not only to gain a command of a particular subject (WHAT content do they need to learn?), but also HOW and WHY they need to learn it.



Author(s):  
Waldemar Karwowski

Objective: In this paper, the author explores a need for a greater understanding of the true nature of human–system interactions from the perspective of the theory of complex adaptive systems, including the essence of complexity, emergent properties of system behavior, nonlinear systems dynamics, and deterministic chaos. Background: Human performance, more often than not, constitutes complex adaptive phenomena with emergent properties that exhibit nonlinear dynamical (chaotic) behaviors. Methods: The complexity challenges in the design and management of contemporary work systems, including service systems, are explored. Examples of selected applications of the concepts of nonlinear dynamics to the study of human physical performance are provided. Results: Understanding and applications of the concepts of theory of complex adaptive and dynamical systems should significantly improve the effectiveness of human-centered design efforts of a large system of systems. Conclusion: Performance of many contemporary work systems and environments may be sensitive to the initial conditions and may exhibit dynamic nonlinear properties and chaotic system behaviors. Human-centered design of emergent human–system interactions requires application of the theories of nonlinear dynamics and complex adaptive system. Application: The success of future human–systems integration efforts requires the fusion of paradigms, knowledge, design principles, and methodologies of human factors and ergonomics with those of the science of complex adaptive systems as well as modern systems engineering.



2019 ◽  
Vol 17 (1) ◽  
pp. 93-109
Author(s):  
Chris Girard

AbstractSpatial boundaries, thermodynamic–economic specialization, and signal processing are at the core of evolution’s major transitions. Centered on these three dimensions, a proposed evolutionary informatics model roots ethnic and racial cleavages in zero-sum contests over rivalrous resources within geophysical sites. As the geophysical boundaries and signal-processing complexity of social systems coevolved, zero-sum contests centered on metropoles extracting resources from hinterlands. In this colonial extraction process, racialization arose from non-market spatial segregation of populations tagged with hinterland lineage. Subsequent post-industrial erosion—and greater permeability—of racial and ethnic boundaries has been enabled by the progressive uncoupling of more highly evolved complex adaptive systems from geophysical location (non-territorial adaptation). Signal and physical topologies are becoming more distinct. This uncoupling from physical location is driven by cybernetic parallelism in complex adaptive systems: diverse and independent agents learning from their mutual exchange of signals. Cybernetic parallelism has generated epistemic and geopolitical challenges to formal apartheid and racializing immigration policies, but not without friction or reversals.



Kybernetes ◽  
2019 ◽  
Vol 48 (6) ◽  
pp. 1330-1354 ◽  
Author(s):  
Maurice Yolles

PurposeComplex systems adapt to survive, but little comparative literature exists on various approaches. Adaptive complex systems are generic, this referring to propositions concerning their bounded instability, adaptability and viability. Two classes of adaptive complex system theories exist: hard and soft. Hard complexity theories include Complex Adaptive Systems (CAS) and Viability Theory, and softer theories, which we refer to as Viable Systems Theories (VSTs), that include Management Cybernetics at one extreme and Humanism at the other. This paper has a dual purpose distributed across two parts. In Part 1, the purpose of this paper is to identify the conditions for the complementarity of the two classes of theory. In Part 2, the purpose is to explore (in part using Agency Theory) the two classes of theory and their proposed complexity continuum.Design/methodology/approachA detailed analysis of the literature permits a distinction between hard and softer approaches towards modelling complex social systems. Hard theories are human-incommensurable, while soft ones are human-commensurable, therefore more closely related to the human condition. The characteristics that differentiate between hard and soft approaches are identified.FindingsHard theories are more restrictive than the softer theories. The latter can embrace degrees of “softness” and it is explained how hard and soft approaches can be mixed, sometimes creating Harmony.Originality/valueThere are very few explorations of the relationship between hard and soft approaches to complexity theory, and even fewer that draw in the notion of harmony.



2019 ◽  
Vol 46 (8) ◽  
pp. 961-984
Author(s):  
Nathan Eckstrand

This article explores the relationship between deliberative democracy, the Internet, and systems theory’s thoughts on diversity. After introducing Habermas’s theory of deliberative democracy and how diversity fits into it, the article discusses various ideas about whether and how it could work on the Internet. Next, the article looks at research into diversity done in the field of complex adaptive systems, showing that diversity has both good and bad effects, but is clearly preferred for the purpose of survival. The article concludes with an analysis of how the results of systems theory’s study of diversity can assist society in bringing democracy to the Web.



2015 ◽  
Vol 2 (1) ◽  
pp. 65-73 ◽  
Author(s):  
David Large ◽  
Petia Sice ◽  
Robert Geyer ◽  
Geoff O'Brien ◽  
Safwat Mansi

In this paper the authors consider two contrasting viewpoints; Complex responsive processes which deal with interactions in the present, and complex adaptive systems which focus on learning through the production of what are called mental models. The paper shows that rather than being contradictory, these viewpoints are – at least in some respects - complementary. From the resulting perspective we are able to identify qualitative synergies between the two approaches. Complex responsive processes involve reflections on interactions that take place in time. But you cannot stop time so these present reflections always refer back to a present now gone. Complex adaptive systems are analytic tools. They are not explicitly in the present or in time at all, but they shape our thoughts and actions which are in the present. They shape how people behave, respond and think in a context. In this way people can combine, or reorganise, the approach to complex responsive processes and complex adaptive systems to show how humans address the complex notions of our world.



Author(s):  
Gr gor S. Pushnoi ◽  
Gordon L. Bonser

Emergent properties of complex adaptive systems (CAS) are explored by means of “agent-based modelling” (ABM), which are compared with results from modelling on the basis of the method of systems potential (MSP). MSP describes CAS as a holistic system whereas ABM-methodology considers CAS as set of interacting “agents.” It is argued that MSP is a “top-bottom” approach, which supplements ABM “bottom-up” modeling of CAS. Adaptive principles incorporated into CAS at the level of a holistic system exploit Lamarck’s ideas about evolution, while the adaptive rules incorporated in the inner structure of CAS reflect Darwin’s ideas. Both ABM and MSP exhibit the same macroscopic properties: (1) “punctuated equilibrium”; (2) sudden jumps in macro-indices; (3) cyclical dynamics; (4) superposition of deterministic and stochastic patterns in dynamics; (5) fractal properties of structure and dynamics; (6) SOC-phenomenon. ABM demonstrates these properties via simulations of the different models whereas MSP derives these phenomena analytically.



2017 ◽  
Vol 26 (1) ◽  
pp. eR01 ◽  
Author(s):  
Susanna Nocentini ◽  
Gérard Buttoud ◽  
Orazio Ciancio ◽  
Piermaria Corona

Aim of study: The paper is a scientific commented discussion with the aim of defining a framework which allows both a comprehensive vision of forest dynamics, as well as an adaptive management approach and policy procedures more suited to a changing and inherently unpredictable world.Main results: We identify the main challenges facing forestry in relation to recent developments in forestry thinking, i.e. the paradox of aiming at sustainability in a changing environment, a shifting perception of the relationship between ecological and social systems, the recognition of forest ecosystems as complex adaptive systems, the need for integrating the social and ecological dimensions of forestry into a single framework, and the growing awareness of the importance of the ethical approach to the forest. We propose the concept of “systemic forestry” as a paradigm for better understanding forest dynamics and for guiding management and public actions at various levels. We compare the systemic approach with different silvicultural and forest management approaches which have been proposed in the last decades.Research highlights: Our analysis shows that a systemic approach to forestry has five main consequences: 1. forestry is viewed as a part of landscape dynamics through a multi-sectoral coordination, 2. the logic of action changes from norm to process, 3. conservation is a dynamic search for resilience, 4. multi-functionality is achieved through a multi-entries approach integrating ecological, social and economic components of sustainability, 5. forestry institutions are reframed to address the issue of changing interactions among actors, 6. a change in the ethical approach to the forest is needed.



PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245096
Author(s):  
Shankar Prawesh ◽  
Balaji Padmanabhan

Algorithms are increasingly making decisions regarding what news articles should be shown to online users. In recent times, unhealthy outcomes from these systems have been highlighted including their vulnerability to amplifying small differences and offering less choice to readers. In this paper we present and study a new class of feedback models that exhibit a variety of self-organizing behaviors. In addition to showing important emergent properties, our model generalizes the popular “top-N news recommender systems” in a manner that provides media managers a mechanism to guide the emergent outcomes to mitigate potentially unhealthy outcomes driven by the self-organizing dynamics. We use complex adaptive systems framework to model the popularity evolution of news articles. In particular, we use agent-based simulation to model a reader’s behavior at the microscopic level and study the impact of various simulation hyperparameters on overall emergent phenomena. This simulation exercise enables us to show how the feedback model can be used as an alternative recommender to conventional top-N systems. Finally, we present a design framework for multi-objective evolutionary optimization that enables recommendation systems to co-evolve with the changing online news readership landscape.



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