Subproject 1: The Paradigm of (Social) Complexity – Part I: Challenges


Some proponents of the Agile movement have tried to associate Agile ideas and practices with the emerging science of complexity (see, for example, [Appelo 2010]). At first glance, this is a plausible connection because in software development, (project) management, and organizations in general, we often have to deal with “complex” (= not simply “complicated”) problems.
But, on closer examination,  the paradigm of (social) complexity isn´t easy to grasp. It´s rather a “tricky beast” because it seems to be as complex as the phenomena (that is, self-organizing dynamic systems and networks)  to be studied themselves.  This means (see also [Wikipedia 2016a,b]):

  1. Many definitions: There is no universally accepted definition of “complexity” or of a “complex system”. And, for various reasons, there will never be such a consensus among complexity researchers. This is true for related  key notions such as “system”, “emergence”, “self-organization / autopoiesis”, etc., too.
  2. Multitude of features: There is an open-ended list of features that may characterize a “complex system”.
  3. Complexity is relative: Complexity can be interpreted as a phenomenon that is in the eye of the beholder. In short, it´s observer-dependent.
  4. Transdisciplinary: There are many scientific disciplines (computer science, physics, biology, psychology, economics, sociology, etc.) involved so that a universal consensus among complexity researchers about the tools, methods, theories, and concepts to be used is  unlikely. This means further:
    First, it´s impossible to give a thorough account of the paradigm of complexity.
    Second, a certain degree of ignorance and non-communication among complexity researchers is to be expected because of various epistemological, theoretical, methodological, and conceptual obstacles that might sometimes be too hard to overcome.
  5. Multiple subdisciplines: Even within a single scientific discipline such as sociology there are various subdisciplines (computational sociology, relational sociology, social network analysis, sociocybernetics, etc.) that are studying complex phenomena.
  6. Multiple approaches: Within each subdiscipline such as sociocybernetics there are various approaches (systems and form theory, 2nd order cybernetics, etc.) with different theoretical options.
  7. Multiple epistemologies: The guiding distinction in this context is constructivism vs realism. But, there isn´t  a single constructivist (or realist) position. Instead, there are many variations of them.

In the following blog posts related to this intro text, I´d like to focus on some of the aspects mentioned above:

  • I´ll start with the definition and feature problems regarding complexity in general (= The Paradigm of (Social) Complexity – Part II: Definitions and Features of Complexity)
  • After that, I´ll narrow the focus and discuss the sociocybernetic approach, esp. the Bielefeld school of sociological systems theory (Niklas Luhmann et al.) related to social complexity (= The Paradigm of (Social) Complexity – Part III: Sociocybernetics).
    This sociocybernetic intro will be quite short because I intend to publish several blog posts later on that discuss many aspects  in more detail (concepts of system, models of communication, social emergence as communication, etc.).
  • And, finally, I´ll present the position of operative constructivism and non-dualism that is crucial for the sociocybernetic / systems theoretical approach presented in this blog  (= The Paradigm of (Social) Complexity – Part IV: Operative Constructivism and Part V: Non-Dualism).

References

 

 

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