The Evolution of Complexity - Abstracts.

The Challenge of Sociocybernetics.

By F. Geyer

  • Felix Geyer
  • Plantage Muidergracht 4
  • 1018 TV Amsterdam
  • Nederland
  • geyer@SISWO.UVA.NL
  • Full Paper


    This paper summarizes some of the important concepts and developments in cybernetics and general systems theory, especially during the last two decades. Its purpose is to show show how they indeed can be a challenge to sociological thinking. Cybernetics is used here as an umbrella term for a great variety of related disciplines: general systems theory, information theory, system dynamics, dynamic systems theory, including catastrophe theory, chaos theory, etc.

    A distinction is made between first-order and second-order cybernetics. First-order cybernetics originated in the 1940's, exemplified an engineering approach, and was interested in system stability, and thus in feedback processes in automata and other machines which further equilibrium conditions and make them amenable to steering efforts. Second-order cybernetics originated in the 1970s, was based on biological discoveries, especially in neuroscience, and was interested more in the interaction between observer and observed than in the observed per se. It has led to a re-evaluation of many of the tenets of mainstream philosophy of science, which was implicitly based on a rather mechanistic and Newtonian clockwork image of the universe, stressed linear causality, and had a preference for order rather than disorder.

    Many of the concepts and procedures of first-order cybernetics admittedly seem useful for sociology: system boundaries; the distinction between systems, subsystems and suprasystems; the stress on circular causality; feedback and feedforward processes; auto- and cross-catalysis, etc. However, second-order cybernetics is more likely to influence sociological thinking in the future.

    This is due, first of all, to its insistence that the interactions between the observer and his subject matter should be included in the system to be studied, which leads to increased attention for phenomena like self-reference. Second, its basis in biology furthers its predilection for change rather than stability, for morphogenesis rather than homeostasis, and this may lead to an increasing stress on self-organization, and to a realistic awareness that sociological phenomena often cannot be forecast, but at best understood. Third, this is caused by autopoiesis (Greek for self-production), the recognition of the fact that all living organisms are self-steering within certain limits, and that their behaviour therefore can be steered from the outside only to a very moderate extent. Fourth, this leads to the continuous emergence of new levels of organized complexity within society, at which new behaviour can be demonstrated and new interactions with the environment become possible.

    Finally, attention is devoted to the emerging "science of complexity" - including neural networks, artificial intelligence, artificial life, etc. - while the methodological drawbacks of especially second-order cybernetics are discussed.