Conference was held in Crakow, Poland. It was organized by Management Process Dept. in cooperation with Research Commitee of Sociocybernetics, International Sociological Association.

In the early 21st  century the challenges of predictability have acquired a new significance. This is caused by an increasing awareness of environmental threats, terrorism, vulnerability of the techno-structure of modern civilization, barriers of strategic management and, last but not least, by the recent turmoil in the financial markets. Summarised as the growing complexity of the world, they lead to questions such as: “Are we living in a risk society?”, “What does the concept of Predictable Surprises mean?”, “Do we have to accept Imperfect Knowledge Economics?”

In such circumstances, the term “complexity”, used frequently as a kind of “buzzword”, has gained a specific role in the language of modern science and policy making. At the same time “complexity scholars”, i.e., the authors claiming to study the complexity of nature and society, purposively or not, directly or not, stimulate expectations of policy making by attributing marketing-like titles to their works and courses – “Hidden Order”, “Harnessing Complexity”, “Order out of Chaos”, “Understanding Complex Organizations” (repeated in various contexts), etc.

The demand from practitioners (policy makers, managers, financiers) on the one hand, and attempts to provide relevant responses made by the academic community on the other, is nothing unusual by itself. A new element in that discourse between practice and “complexity studies” is resulting from awareness of the limited possibility, or even impossibility, of the prediction of social phenomena, especially at macro- and meso - scales. Such an epistemological pessimism can be acceptable in academic discourse but cannot  be  transferred  to  practice.  Economic,  social  and  environmental policy,  and finance and management are most representative examples of the areas in which prediction is a foundation for actions, where an “early warning” is so metimes essential.

Many problems arise in defining terms associated with “studies of complexity”, “complex systems studies” and the like. Terms such as artificial life, fractals, bifurcations, co-evolution, spontaneous self-organization, self-organized criticality, chaos, edge of chaos, instability, irreducibility, adaptability, far-from-equilibrium-states are now widely used. In his search for explaining the meaning of complexity in 1989, Lloyd identified 31 definitions of complexity; later, according to Horgan, this number increased to 45 – many of them following a quantitative approach. Therefore, complementary to the advancement of quantitative “complexity sciences”, the exploitation of theories/principles already elaborated within cybernetics and systems thinking is advisable.

The first attempts to study complex entities go back to the works of Weaver (disorganized complexity and organized complexity), Simon (the Architecture of Complexity), Ashby (the Law of Requisite Variety) and Wiener and others (on self- organisation).

In the social sciences, and particularly in sociology, special attention is given to the concept  of  the  complexity  of  social  systems  proposed  by  Luhmann  for  whom complexity is strongly linked to self-observation. This phenomenon is representative of the epistemology of modern social sciences, where observation and self-observation, reflexivity and self-reflexivity, and, subsequently, self-reference are playing a growing role. According to this interpretation, social systems are becoming self-observing, self- reflexive entities trying to solve arising problems through the processes of adaptation (learning).

A question thus arises. If unpredictability or low reliability of prediction is the key feature of the complexity of social phenomena, what ideas drawn from sociocybernetics can help the social sciences in achieving a better understanding of change in modern society? This question is of a special significance in policy-oriented sciences dealing with social phenomena – economics, management, finance and security studies, which aim, not only at description and explanation, but also at providing guidance for action.