New Science Of Complexity Research Articles

A Context for Complexism: Between Neoliberal Social Thought and Algorithmic Art

Abstract Among the many genres of visual art to emerge in the wake of computerisation, the subset of generative or algorithmic art known as complexism seems uniquely keyed to the social and technological mainsprings of everyday life in the twenty-first century. Complexism typically deploys computer algorithms to demonstrate how complex phenomena can emerge through the reiterative enactment of simple rulesets. The light and sound installations and the videos that complexist artists produce, alongside the discourses surrounding the works, stand out as singularly contemporary, not necessarily for their exploitation of now-ubiquitous telematic tools and techniques, but for their deep commitment to the trailblazing problems, methods, and hypotheses set out by the new science of complexity. Practitioners of and commentators on complexism (the work and writings of Philip Galanter feature most prominently here) persistently invoke this booming interdisciplinary field of complexity research. Against this trend, I argue that for all the leverage the tools and terms of complexity science supply to complexist art, the concept of complexity itself remains surprisingly vague and shorn of any historical sensibility. One preliminary aim of this essay is to bring more theoretical rigour to the artists’ use of this concept by beginning to fill in the missing backstory. From there, I move to complicate this genealogy by introducing a somewhat controversial figure-the social theorist, political economist, and legal philosopher Friedrich Hayek, who had posited similar problems concerning the emergence and maintenance of complex, self-organized systems as early as the 1930s, and whose theoretical solutions to these problems were instrumental to what historians and sociologists have subsequently described as capitalism’s late “neoliberal turn.”

Classical Mechanics, Complexity and the Methodology

Research on complexity has exploded in recent years, despite the lack of mature theoretical and computational tools. By refining the concepts from complex systems and classical mechanics, here we propose that the methodology developed in classical mechanics over the last four centuries, together with those from other disciplines, might once again nurture the new science of complexity in the coming years.

Can the new cosmology, cosmogenesis, serve as a basis for a shared value system in architecture? On Charles Jencks

According to the architectural theorist Charles Jencks, a major problem in architecture at this moment is the spiritual crisis, and the loss of a shared metaphysics. He believes that it is the task of architects to take responsibility for the public and esoteric meanings of a civic building, although this is an especially difficult task in a global culture where many believe there is no shared value system. Jencks is aware of the problem but at the same time he believes that a new paradigm in architecture is emerging. He describes this new paradigm as follows:We have moved from a mechanistic view of the universe to one that is self-organising at all levels from the atom to the galaxy. Illuminated by the computer, this new worldview is paralleled by changes now occurring in architecture.Jencks concedes that this shift in worldview is only beginning, that there is no widespread cultural movement under way, but one can discern the beginnings of a shift in architecture that relates to a profound transformation in science. Jencks is particularly interested in new sciences of complexity: fractals, nonlinear dynamics, self-organising systems, and the new cosmology. At the core of this new worldview is the new cosmology, ‘cosmogenesis’, which reveals the universe as a single, unfolding, creative event perpetually striving for new levels of self-organisation. Cosmogenesis tells us a new story of the universe and therefore Jencks perceives it as our new Genesis.

Equilibrium Illusion, Economic Complexity and Evolutionary Foundation in Economic Analysis

It is widely believed that an equilibrium framework based on simple models, such as the representative agent and bilateral bargaining, in a frictionless economy provides a consistent framework in micro, macro, finance, and institutional economics. However, equilibrium believes in self-stabilizing market and institutional convergence broken down when inherent instability and non-predictable uncertainty emerge under nonlinear and social interactions. Equilibrium illusions in economics and econometrics are pretty in math modeling but dangerous in policy decision. Known examples are the Frisch model of noise-driven cycles, the Lucas model of microfoundations, and the Coasian world of zero transactions. These models not only violate basic laws in science but also lack evidence in economic history. Their common problem is associated with linear Hamiltonian economics with symmetric information without history. Economies are dissipative systems in nature, characterized by symmetry breaking, information flow, a time arrow, and history. The many-body problem is fundamentally different from the one-body and two-body problem in mathematics. Both computational and natural experiments, such as a stock market crash and a transitional depression, reveal the severe limitations of equilibrium thinking and structural changes from evolutionary dynamics. The new science of complexity offers new tools of nonlinear dynamics and non-stationary time series analysis. Existing puzzles in equilibrium economics, such as persistent cycles, interruptive crises, market resilience, social movements, and organizational diversity, can be better understood by nonlinear dynamic models. Like the paradigm shift after Einstein in physics, the evolutionary perspective provides a general framework, while equilibrium models serve as its special cases, since the equilibrium picture is an approximation of economic complexity in a short-time window taken from a long-term historical current.

Investigating Current Social, Economic and Educational Issues using Framework and Tools of Complexity Science

There exists compelling evidence that as evolution follows its course the complexity of our social, economic, educational and cultural environments increases. Methods and tools that were suitable for resolving issues arising in stable environments are not effective under conditions of uncertainty created by the occurrence of frequent, unpredictable events. The new Science of Complexity offers a framework and software tools for resolving issues which change during the problem-solving process. The power of Complexity Science concepts (self-organisation, emergence, autonomy, evolution, adaptation) backed by intelligent software tools is illustrated by a variety of case studies from the author's rich experience as a researcher and practitioner, including large-scale logistics, social security provision, fraud detection, security screening, data mining, knowledge discovery, education and many others.

6.3.3 Practical Applications of Complexity Theory for Systems Engineers

AbstractThis paper provides a basic background in chaos and complexity theory and shows systems engineers how to improve the way they work in accordance with their increased awareness of the complex nature of systems, enterprises, and the environment. As systems and the enterprises in which they are developed become increasingly complex, systems engineering as learned and taught in the twentieth century should be supplemented by principles learned in the new sciences of complexity and chaos. Awareness of complexity theory can help practicing engineers perform their tasks differently on projects, in ways ranging from understanding the problem space and making models of the environment early in the life cycle, through managing changing requirements, designing differently, and identifying and managing risks, to supporting changing project management approaches.In addition, a science of complex systems engineering is being formed. This involves developing a formal theoretical backdrop for the heuristics that systems engineers have experientially found effective in architecting and developing complex systems. Complexity theory is enriching efforts to develop this advanced system engineering approach and practices.

Computability and Evolutionary Complexity: Markets as Complex Adaptive Systems (CAS)

Few will argue that the epi-phenomena of biological systems and socio-economic systems are anything but complex. The purpose of this Feature is to examine critically and contribute to the burgeoning multi-disciplinary literature on markets as complex adaptive systems (CAS). The new sciences of complexity, the principles of self-organisation and emergence along with the methods of evolutionary computation and artificially intelligent agent models have been developed in a multi-disciplinary fashion. The cognoscenti here consider that complex systems whether natural or artificial, physical, biological or socio-economic can be characterised by a unifying set of principles. Further, it is held that these principles mark a paradigm shift from earlier ways of viewing such phenomenon.

THE ORIGINS AND GOVERNANCE OF COMPLEX SOCIAL SYSTEMS

The new science of Complexity explains that limited knowledge prevents societies from predicting and controlling their developments. But Complexity further suggests that nature uses the limits of knowledge to evolve, which turns an apparent obstacle into an opportunity to reevaluate governmental institutions. As in nature, the limits of knowledge lead social systems to evolve by individuating, liberating, and empowering their members. Societies individuate and liberate their members to probe environments and exploit opportunities. Societies empower individuals to globalize their findings which requires constitutionally constraining governmental powers. Societies that respect human rights thus gain selective advantage. Showing that what nature is models what societies ought to be, Complexity may finesse the “naturalistic fallacy” of Hume and Moore.

WHERE IS MORIN'S ROAD TO COMPLEXITY GOING?

Edgar Morin took an early lead within the French intellectual community, but also in comparison with parallel reflections in the English-speaking world, as far as critical discussion of the epistemology of the new sciences of complexity is concerned. His “complex thought” raises many intriguing questions and offers a dazzling synthesis of a wide range of fields, from physics to biology to psychology and the social sciences. However, Morin's road to complexity bypasses some crucial issues in philosophy and political economy. Therefore, although Morin's insights remain invaluable, one has reasons to be a little skeptical about the exact nature of the reform of thought he has sketched out.

Navigating in a complex nursing world.

The recent findings emerging from the new science of complexity are altering our view of unpredicted behavior. In many cases, natural laws hidden deep within the complex processes of healthcare systems may be exerting a powerful influence over our ability to control outcomes. The author explores the concept of complexity and how nurse administrators may use these new theories to navigate through an increasingly unpredictable world.

Theology and psychology: an essay review on Fraser Watts

In his recent book Theology and Psychology, Fraser Watts explores an area of interdisciplinary dialogue that has become active on many fronts. He traces the main areas of engagement while limiting his purview mostly to psychological explorations of the formation of the human spirit and of religious experience, and theology directed to parallel concepts. Psychology is largely pursued within its subdisciplines pertaining to introspective psychologies, neuroscience, and social psychology. The theology is mostly within the Christian, and especially Anglican, tradition, yet the variety of voices here is also well known. Within these broad limits, and with impressive depth and breadth of scholarship, Watts addresses topics as diverse as evolutionary theory, the nature of consciousness, artificial intelligence, the foundations of morality, the soul, immortality, divine action, the doctrine of the Fall, eschatology, and the origin of belief. Although he provides fair representations of various views, he consistently rejects 'greedy' forms of 'nothing buttery', because he believes that the human person and religious experience are so multifaceted that they cannot be grasped from any single standpoint. In addition, as he points out, various reductionistic claims are simply inaccurate. It is suggested that Watts's thinking shows many parallels with theories developing within the new sciences of complexity. Further development of his work along these lines might have significance both for his own contribution and for the growing field of complexity studies.

Complex Acts of Knowing: Paradox and Descriptive Self‐Awareness

We are reaching the end of the second generation of knowledge management, with its focus on tacit-explicit knowledge conversion. Triggered by the SECI model of Nonaka, it replaced a first generation focus on timely information provision for decision support and in support of BPR initiatives. Like BPR it has substantially failed to deliver on its promised benefits. The third generation requires the clear separation of context, narrative and content management and challenges the orthodoxy of scientific management. Complex adaptive systems theory is used to create a sense-making model that utilises self-organising capabilities of the informal communities and identifies a natural flow model of knowledge creation, disruption and utilisation. However the argument from nature of many complexity thinkers is rejected given the human capability to create order and predictability through collective and individual acts of freewill. Knowledge is seen paradoxically, as both a thing and a flow requiring diverse management approaches. The Cynefin Centre Membership of the Centre, which focuses on action research in organisational complexity is open to individuals and to organisations. It focuses on high-participation action research projects seeking new insights into the nature of organisations and markets using models derived from sciences that recognise the inherent uncertainties of systems comprised of interacting agents. However, the Centre is not about attempting to apply physical or biological models to organisations wholesale without attention to the uniquely human capacities of free will, awareness and social responsibility. It is about engaging human organisational complexity in its many manifestations, including the ancient collective and emergent patterns of narrative, ritual, negotiation of identity and truth, self-representation and knowledge exchange. The Centre is not about consultants or academics conducting multiple interviews or observations and deriving static hypothesises and models based on their outside "expertise". It is about creating focused dynamic interactions between traditional and unexpected sources of knowledge to enable the emergence of new meaning and insight. The Centre is based on a model of networked intelligence, creating a broad and loosely structured coalition of academics, industrial and governmental organisations to create new insight and understanding for its members into the complexity of managing in a new age of uncertainty. The basis of all Centre programmes is to look at any issue from multiple new perspectives and to facilitate problem solving through multiple interactions among programme participants. Programmes run on a national, international and regional basis and range from investigation of seemingly impossible or intractable problems to pragmatic early entry into new methods and tools such as narrative databases, social network stimulation and asymmetric threat response.

Repercussions of complex adaptive systems on product design management

Product design management is becoming an increasingly important concept. However, there is no generally accepted agreement as to exactly what activities this management involves. We therefore put forward the need to link design management with other convergent theoretical approaches that clarify and improve an understanding of the concept. In this study, we look at the implications of the ideas involved in complex adaptive systems, steeped in the new science of complexity, for product design management. Following on from this, we highlight four product design management activities: strengthening the relationships between firm members and the outside, fostering relationships between areas or people within the process of product design, increasing information flow to a maximum, and promoting a balanced heterogeneous participation in design decision making.

Prevention of alcohol problems in the 21st century: challenges and opportunities.

The community is the "new frontier" for alcohol and other drug prevention. New prevention initiatives at the community level suggest that effective strategies will often be quite different from national or state policies and will require a different perspective. Alcohol and other drug use is part of routine community life and must be considered in the context of the community, which is itself a dynamic and self-adapting system. To develop effective community-level interventions, prevention planners and policy makers must understand how various aspects of the community influence alcohol and other drug use and even contribute to alcohol and other drug problems. This paper outlines the basis for a systems approach to community prevention and the policy options that this approach suggests. It also examines the new science of complexity, differentiates between catchment and a systems approach to prevention, describes a public health model within a systems approach, and describes using local policy as a means to produce system changes as well as recent findings from community-based prevention efforts that employed local alcohol policies.

What organizational leaders should know about the new science of complexity

What organizational leaders should know about the new science of complexity

Strategy, dynamic capabilities and complex science: management rhetoric vs. reality

The dynamic capabilities approach (DCA) has dominated strategic analysis in the 1990s. It can offer a compelling explanation of competition, relative corporate performance and strategic decision-making. The strengths of DCA are essentially in its use for historical explanation and its use in strategy formation is limited and possibly erroneous. There is still a need for a theory of strategy that will offer better application and guidance for practitioners. Analogies are drawn from the new science of complexity for identifying and shaping strategic decisions. Copyright © 2000 John Wiley & Sons, Ltd

Patterns in the sand: computers, complexity, and everyday life

From the Publisher: Until recently, science has made progress by breaking large systems down into smaller and simpler parts, studying and explaining how these parts operate, and putting them back together again. Although this approach works amazingly well when we study the atom or the function of a single gene, it hits a brick wall when it comes to vastly complex systems like the brain, or the weather, or the ecosphere. Such systems are just too complicated to yield their secrets to the reductionist approach. The new science of complexity, one of the twentieth century's greatest contributions to our comprehension of nature, is concerned with treating vastly complicated systems, like the biosphere or the Internet, as holistic systems. Patterns in the Sand discusses this new scientific paradigm that treats life as a natural computation, and shows how this approach translates into ways of dealing with complexity in real life. Using such everyday phenomena as illustrations, Bossomaier and Green take us from the most basic function of the simple Turing computer through the vast interrelationships of the earth's biota right up to the search for life on other planets, while providing a new understanding of the complicated, complex, world around us.

Complexity in Manufacturing: Some Lessons to Learn in Planning and Implementation

This paper by Sunderraman explains the need to complement the reductionism of planning' with the holism of ‘learning’ from the perspective of the new science of complexity. The interconnectedness, nonlinearity, discontinuity, feed back loops and human interventions make manufacturing a complex adaptive system. Inherent complexity and random perturbations cause unpredictable fluctuations in manufacturing at all levels. The learning heuristics of adaptive system can effectively tackle situations in manufacturing where the underlying cause structure is unknowable or difficult to isolate. The basic understanding of the tenets of chaos and complexity helps respond to manufacturing reality. The appreciation of real-time learning as a useful complement to planning will bridge the growing divide between implementors and planners in manufacturing.

Diving Into Complexity: Developing Probabilistic Decentralized Thinking Through Role-Playing Activities

There is a growing interest in role-playing activities, both in school classrooms and in the culture at large. Despite this growing interest, role-playing activities are rare in mathematics and science classrooms. In social-studies activities, a major goal is to help students adopt the perspective of another person. However, mathematics and science classes typically discourage this type of perspective-taking; science is usually taught as a process of detached observation and analysis of phenomena, not active participation within phenomena. In this article, we argue that role-playing activities can play a powerful role in mathematics and science education—particularly in the study of the new sciences of complexity. We present detailed descriptions and analyses of 2 role-playing activities that we have organized. Each activity is designed to help students explore (in a very participatory way) the behaviors of complex systems, helping them develop better intuitions on how complex phenomena can arise from simple interactions, and predictable patterns from random events.

Complex Adaptive Systems, Evolutionism, and Ecology within Anthropology: Interdisciplinary Research for Understanding Cultural and Ecological Dynamics

We now know that far from equilibrium, new types of structures may originate spontaneously. In far-from-equilibrium conditions we may have transformation from disorder, from thermal chaos, into order. New dynamic states of matter may originate, states that reflect the interaction of a given system with its surroundings. We have called these new structures dissipative structures to emphasize the constructive role of dissipative processes in their formation. -Prigogine and Stengers 1984:12 A Science of Complex Systems Recently the ecologist C.S. Holling has discussed the conflict between two streams of and the confusion it creates for politicians and the public (Holling 1995:12-16; see also Holling 1993:553-4). One stream is experimental, reductionist, and narrowly disciplinary. It is familiar to us as the scientific ideal. The less familiar stream is interdisciplinary, integrative, historical, analytical, comparative, and experimental at appropriate scales. Examples given of the first form are molecular biology and genetic engineering. The second form is found in evolutionary biology and systems approaches in populations, ecosystems, landscapes, and global dynamics. One stream is a science of parts, the other a science of the integration of parts. Anthropology has held itself up to the first stream ideal of science. But the first stream ideal does not always produce the results in anthropology that proponents and critics alike have demanded. Our knowledge of detail is incomplete at societal scales, and prediction can fail. Disproof by experiment is unlikely even with natural experiments. And unanimous agreement over results is almost never reached. One response by anthropologists has been to shrink temporal and spatial scales, and hold fast to the ideal; to let the requirements of the scientific methods of this first stream of science structure our research. Anthropologists are often dissatisfied with such restrictions on our object of study, but see little alternative if anthropology is to become a mature science. But science itself is always evolving. Many anthropologists, both proponents of science and critics, are unaware of the constructive critiques now coming from the mature disciplines of science, from the hard sciences. For over twenty years scientists like Holling and Nobel prize chemist Ilya Prigogine (Prigogine 1980, Prigogine and Stengers 1984) have been arguing that the first stream of science is limited to certain problem sets. They contend that a science of complexity has fundamentally different features, and is the proper approach to other problem sets. The subject matter of anthropological inquiry, it will be shown, is commonly addressed in problem sets of the second type. In fact, anthropologists long have argued their case for understanding cultures in terms that sound remarkably like those advocated by the new science of complexity. We have been righting to resemble the ideal of science, while a second form is coming to look like us. Points for Anthropology Holling identifies a number of characteristics of the integrative stream of science. It incorporates technologies and results from reductionist, experimental science, but does not expect disproof by experiment and ultimate agreement by the scientific community. Models are multivariate and multi-scaled, and testing of alternative hypotheses is done by planned and unplanned interventions into whole systems in case studies, with the evaluation of the integrated consequence of each alternative. Multiple lines of converging evidence are used to argue for one hypothesis over another in a process of peer assessment and judgment. While these ground rules for research might be revolutionary in the physical sciences, anthropology has long been forced by our subject into this type of science. Case study ethnographies are our hallmark. Experimental disproof is difficult and uncertainty is high. …