Systems Theory/Cybernetics

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What is Cybernetics?[edit | edit source]

There are many different definitions of Cybernetics and many individuals who have influenced the direction of Cybernetics. Cybernetics takes as its domain the discovery or design and application of principles of regulation and communication. Cybernetics treats ways of behaving and not things. Cybernetics does not ask "what is this thing?" but "what does it do?" and "what can it do?" However, questions may also be posed concerning "how it does what it does" which is reflected in higher orders of cybernetics. Because numerous systems in the living, technological and social world may be understood in this way, Cybernetics is a combination of many traditional disciplines. The concepts which Cyberneticians develop thus form a metadisciplinary language through which we may better understand and modify complex systems.

History[edit | edit source]

Deriving from the Greek word for steersman (kybernetes), Cybernetics was first introduced by the mathematician Wiener, as the science of communication and control in the animal and the machine (to which we now might add: in society and in individual human beings). It grew out of Shannon's information theory, which was designed to optimize the transfer of information through communication channels (e.g. telephone lines), and the feedback concept used in engineering control systems. A more philosophical definition, suggested in 1958 by Louis Couffignal, one of the pioneers of Cybernetics in the 1930s, considers Cybernetics as "the art of assuring efficiency of action". Cybernetics in General Systems Theory is defined as the study of control within a system, typically using combinations of feedback loops. This can be within machines or living structures. First order Cybernetics relates to closed systems, second order includes the observer perspective and third order looks to how these co evolve.

Cybernetics and systems theory study basically the same problem, that of organization independent of the substrate in which it is embodied. Insofar as it is meaningful to make a distinction between the two approaches, we might say that systems theory has focused more on the structure of systems and their models, whereas Cybernetics has focused on how systems function, that is to say how they control their actions, how they communicate with other systems or with their own components. Since structure and function of a system cannot be understood in separation, it is clear that systems theory and Cybernetics should be viewed as two facets of a single approach.

Cybernetics Contributions[edit | edit source]

The early contributions of Cybernetics were mainly technological, and gave rise to communication technology, feedback control devices, automation of production processes and computers. Another tradition, which emerged from human and social concerns, emphasizes epistemology, how we come to know, and explores theories of self-reference to understand such phenomena as identity, autonomy, and purpose. Some Cyberneticians seek to create a more humane world, while others seek merely to understand how people and their environment have co-evolved. Some Cyberneticians are interested in systems as we observe them, others in systems that do the observing. Some try to develop methods for modelling the relationships among measurable variables. Others seek to understand the dialogue that occurs between models or theories and social systems. Early efforts sought to define and apply principles by which systems may be controlled. More recently, Cyberneticians try to understand how systems describe themselves, control themselves, and organize themselves. Despite its short history, Cybernetics has developed a concern with a wide range of processes involving people as active organizers, as autonomous, and as sharing communicators, responsible individuals. Interest moved soon to numerous sciences, applying Cybernetics to processes of cognition, to such practical pursuits such as psychiatry, family therapy, the development of information and decision systems, government, management, and to efforts to understand complex forms of social organization including communication and computer networks.

Pillars of Cybernetics[edit | edit source]

Cybernetics theories tend to rest on four basic pillars: circularity, variety, process and observation. Circularity occurs in its earliest theories of circular causation or feedback, later in theories of recursion and of iteration in computing and now involving self-reference in cognitive organization and in autonomous systems of production. This circular form enables Cybernetics to explain systems from within, making no recurse to higher principles or a priori purposes, expressing no preferences for hierarchy. Variety is fundamental to its communication, information and control theories and emphasises multiplicity, alternatives, differences, choices, networks, and intelligence rather than force and singular necessity. Almost all Cybernetic theories involve process and change, from its notion of information, as the difference between two states of uncertainty, to theories of adaptation, evolution and growth processes. A feature of Cybernetics is that it explains such processes in terms of the organization of the system manifesting it, e.g., the circular causality of feedback loops is taken to account for processes of regulation and a system's effort to maintain equilibrium or to reach a goal. Observation including decision making is the process underlying Cybernetic theories of information processing and computing. By extending theories of self-reference to processes of observation including cognition and other manifestations of intelligence, Cybernetics has been applied to itself and is developing an epistemology of systems involving their observers (second-order Cybernetics) qualitatively unlike the earlier interest in the ontology of systems which are observed from the outside (first-order cybernetics).

Focus[edit | edit source]

While as a meta-theory, the principles and ideas of Cybernetics and Systems Science are intended to be applicable to anything, the "interesting" objects of study that Cybernetics and Systems Science tends to focus on are complex systems such as organisms, ecologies, minds, societies, and machines. Cybernetics and Systems Science regards these systems as complex, multi-dimensional networks of information systems. Cybernetics presumes that there are underlying laws and principles which can be used to unify the understanding of such seemingly disparate types of systems. The characteristics of these systems directly affect the nature of cybernetic theory, resulting in serious challenges to traditional methodology. Some of these characteristics are complexity, mutuality, complementarity, evolvability, constructivity and reflexivity (for additional information consult the appendix). The domain of computing applications has grown so rapidly that labelling anything that uses a computer as "cybernetic" is more obscuring than enlightening. Therefore we would limit the label "cybernetic technology" to those information processing and transmitting tools that somehow increase the general purpose "intelligence" of the user, that is to say the control the user has over information and communication.

The systemic and the analytic approaches are more complementary than opposed, yet neither one is reducible to the other. The analytic approach seeks to reduce a system to its basic elements in order to study in detail and understand the types of interaction that exist between them. By modifying one variable at a time, it tries to conclude general laws that will enable one to predict the properties of a system under very different conditions. To make this forecast possible, the laws of the additivity of elementary properties must be invoked. This is the case in homogeneous systems, those composed of analogous elements and having weak interactions among them. Here the laws of statistics readily apply, enabling one to understand the behaviour of the multitude of disorganized complexity. The laws of the additivity of elementary properties do not apply in very complex systems composed of a large diversity of elements linked together by strong interactions. These systems must be approached by methods such as those which the systemic approach groups together. The purpose of the new methods is to consider a system in its complexity, its totality, and its own dynamics. Through simulation one can "animate" a system and observe in real time the effects of the different kinds of relations among its elements. The study of this behavior leads in time to the determination of rules that can modify the system or design other systems.

Resources and Further Reading[edit | edit source]