Posts Tagged ‘autopoiesis’
This essay attempts to explain through an analysis of the limitations of the Lakoff, Johnson and Turner school of cognition and meaning-making, why exactly Arakawa and Gins’ analogical relations with the cognitive science of Maturana and Varela and the philosophy of mind of Gilles Deleuze offer a pair of conceptual/analogical landing sites that enables them to move beyond cognitive science and philosophy of mind to a profound reconfiguration of art and ethics.
We find an embrace of a model of cognitive functioning which, while recognizing top-down behavior (and its socio-cultural correlates), signals an investigation into bottom-up emergent properties. The term emergent properties refers to processes of self-organization with two related properties—distributed and enactive—which force the analysis of even single organisms as societies united through spontaneous cognitive activity. Whether talking analogically about connectionist computer architecture, the behavior of organic neural nets, aggregating natural and artificial life forms, or models of distributed “social” cognition, “mind,” and its behavior, become understood not as that which controls the body, but as that which results spontaneously as embodied cognitive processes emerging locally, and then producing global effects. For the human corpus, we refer to processes of cognition located in the senses, the nervous systems, muscles, endocrine system and the individual organs of the body. In particular, we may find analogical explorations of these issues in the philosophy of Gilles Deleuze, whose smooth and striated spaces of the Body Without Organs bears a strong resemblance to the distinction between bottom-up and top-down cognitive processes.
Cybernetic pioneer Warren McCullough asked: “What is a man, that he may know a number; and what is a number, that a man may know it?” Thinking along much the same lines, my question here is: “What is a creative mind, that it might emerge from a complex system; and what is a complex system, that it might give rise to a creative mind?” Complexity science is a fashionable topic these days. My perspective on complexity, however, is a somewhat unusual one: I am interested in complex systems science principally as it reflects on abstract mathematical, computational models of mind. In my three previous books, The Structure of Intelligence, Evolving Mind, and Chaotic Logic, I have outlined a comprehensive complex-systems-theoretic theory of mind that I now call the psynet model. This book is a continuation of the research program presented in my previous books (and those books will be frequently referred to here, by the nicknames EM and CL). One might summarize the trajectory of thought spanning these four books as follows. SI formulated a philosophy and mathematics of mind, based on theoretical computer science and the concept of “pattern. ” EM analyzed the theory of evolution by natural selection in similar terms, and used this computational theory of evolution to establish the evolutionary nature of thought.
The aim of this paper is to outline some foundational aspects of a theory of self-organising social change. Synchronous social self-organisation is based on a contradiction between structures and actors that produces emergent results. The cycle of expanded reproduction of capital outlined by Marx can be interpreted as economic type of autopoiesis or self-reproduction. Aspects of Marxist crisis theory can be incorporated consistently into the framework of a theory of social self-organisation. Capitalism is a complex, evolutionary, antagonistic system that is shaped by a dialectic of chance and necessity: In diachronic social self-organisation of capitalism, the evolving economic, political and cultural antagonisms as objective conditions of existence again and again result in phases of crisis and instability where the future development of the system is highly undetermined. The objective structures condition a field of possibilities, it is not pre-determined which alternative will be taken. In such phases of crisis and bifurcation, agency and human intervention play an important role in order to increase the possibility that a certain desirable alternative will be taken. Certainty can’t be achieved, but agency also is not made impossible by the principles of self-organising social change. The whole movement of social self-organisation is based on a dialectic relationship of chance and necessity. Regulation theory sees the development of system shaped by a dialectic of chance and necessity as well as by a dialectic of generality and specificity in the same manner as self-Organisation Theory. Mechanistic, reductionistic, economistic and deterministic arguments that have been characteristic for traditional crisis theories are avoided, a crisis of society is not reduced to economic factors and to a single economic antagonism. Regulation theory rather considers besides economical also political and ideological factors as relatively autonomous ones that influence crises of society. An unity of a regime of accumulation and a mode of regulation that is characteristic for a specific mode of development that is shaped by a specific structure of antagonisms is assumed. There are distinct parallels between the regulation approach and self-organisation theory, but the relationship between general and specific categories as well as between chance and necessity is still largely unsettled in the regulation approach (as well as in systems theory). It seems that the regulation school assumes a development of capitalism that is largely shaped by random evolution of antagonistic structures that is not dialectically related to general categories and antagonisms. Nonetheless regulation theory gives us a detailed analysis of Fordism, its crisis and Postfordism as well as a very useful model of the development of society. Hence my own approach is partly based on this theory.
Knowledge and the communication of knowledge are critical for self-sustaining organizations comprised of people and the tools and machines that extend peoples’ physical and cognitive capacities. Humberto Maturana and Francisco Varela proposed the concept of autopoiesis (“self” + “production”) as a definition of life in the 1970s. Nicklas Luhmann extended this concept to establish a theory of social systems, where intangible human social systems were formed by recursive networks of communications. We show here that Luhmann fundamentally misunderstood Maturana and Varela’s autopoiesis by thinking that the self-observation necessary for self-maintenance formed a paradoxically vicious circle. Luhmann tried to resolve this apparent paradox by placing the communication networks on an imaginary plane orthogonal to the networked people. However, Karl Popper’s evolutionary epistemology and the theory of hierarchically complex systems turns what Luhmann thought was a vicious circle into a virtuous spiral of organizational learning and knowledge. There is no closed circle that needs to be explained via Luhmann’s extraordinarily paradoxical linguistic contortions.
We begin by describing the importance of emergence and the need, in certain situations, to move away from a reduction mind-set to a more holist approach. We define the term emergence in context of self-organizing systems, autopoiesis and chaotic systems. We then examine a field that is commonly used to explore emergence and selforganization, namely agent and multi-agent systems. After an overview of this field, we highlight the most appropriate aspects of agent research used in aiding the understanding of emergence. We conclude with an example of our recent research where we measure agent emergent performance and flexibility and relate it to the make-up of the agent organization.
Knowledge-based communities are important but poorly understood systems for helping enterprises maintain their organizational integrity and address organizational imperatives. Based on an autopoietic theory of organization, we examine the emergence and development of knowledge-based communities at different scales up to large distributed enterprises and industry clusters. Knowledge-based communities are highly complex systems that evolve and mature through the phased emergence of new features and capabilities. Development and support of successfully sustainable communities needs to be based on a better understanding of how these features and capabilities emerge. To comprehend the impact of emergent behavior within and beyond organizational communities requires an understanding of the social or sociological aspects of a system in relation to the explicit formal/physical structures in the organization.
Humberto Maturana. My purpose in this article is to present a theory of the organization of living systems as autonomous entities, and a theory of the organization of the nervous system as a closed network of interacting neurons structurally coupled to the living system to whose realization it contributes. The fundamental feature that characterizes living systems is autonomy, and any account of their organization as systems that can exist as individual unities must show what autonomy is as a phenomenon proper to them, and how it arises in their operation as such unities. Accordingly the following is proposed. That autonomy in living systems is a feature of self-production (autopoiesis), and that a living system is properly characterized only as a network of processes of production of components that is continuously, and recursively, generated and realized as a concrete entity (unity) in the physical space, by the interactions of the same components that it produces as such a network. This organization I call the autopoietic organization, and any system that exhibits it is an autopoietic system in the space in which its components exist; in this sense living systems are autopoietic systems in the physical space.
Luhmann’s autopoietic theory offers a theory without a priori defined drivers of novelty. Such assumptions has led to claims that Luhmann’s theory is relevant only to the study of routines and not to innovative processes, and that it prevents a satisfactory understanding of the phenomenon of innovation. We would argue differently, and say that autopoietic theory offers a way of conceptualizing how systems reproduce themselves in the face of novelty, further that it is the expected possibility of connecting to novelty that drives systems forward. The possibility of novelty is a central part, both of reproducing central features, and producing features for future operations. Possibilities for novelty arise as systems, as part of their recursive reproduction, draw distinctions amid a changing environment. The system reproduces itself recursively, pointing forward to possible connections, and at the same time connecting to previous operations. It is in this sense that a system may be understood as a ‘‘historical machine’’, or a ‘‘system-in-an-environment-with-a-history’’. We would argue that an autopoietic theory of organization is in fact also a theory of innovation. Without the possibility of novelty, autopoietic organization is hardly possible.