Complexity Theory: Developing a Complexity Lens – Part 1.

David Aron, MD, MS  December 28, 2015.

Complexity is popular, made so by novels and films such as Jurassic Park and mass market non-fiction like Chaos: Making a New Science, and Complexity: The Emerging Science at the Edge of Order and Chaos, and many others. The field has been a rich source of metaphors, some more apt than others, and the terminology has been used to put a scientific veneer on evidence light (if not evidence free) opinions and unsophisticated analyses.  Nevertheless, there have been many efforts to advance the field, usually within traditional disciplines, but sometimes in a more transdisciplinary fashion.

The first problem comes with the definition. There are many definitions and descriptions of complex systems.  Melanie Mitchell’s definition has the virtue of brevity and clarity (at least superficially). She defines complex systems as “collections of elements, interacting nonlinearly, which produce emergent behavior.” The only problem with this definition is the use of the words: collections, elements, interacting, nonlinear, produce, and emergent behavior. How these terms are defined and characterized makes a great deal of difference. Nevertheless, although complexity theory/science is still relatively immature, there is still much of value to be learned. It has been argued by David Byrne that the “complexity frame of reference” was a more apt term. This approach was also endorsed by Boulton, Allen, and Bowman. Different scholars and practitioners have parsed complexity in different ways. Several have listed components, while others have divided complexity into broader categories that included several elements. Morin, a philosopher, divided the field into restricted complexity (a scientific and methodological approach) and generalized complexity (a philosophical and epistemological approach).  Manson, a geographer, divided the field into algorithmic, deterministic, and aggregate complexity. Geyer and Rahani, policy scientists divided complex systems into physical, biotic, and conscious.  Another approach would be to divide the field into academic versus experienced complexity (after Beautement and Broenner).

One of the issues is the separation between what might be termed academic complexity and what we experience as complexity.   In much of the academic literature complexity is approached primarily with mathematical models. This is a consequence of the hegemony of “science” and the particular view that rules in the groves of Academe.  These mathematical models are both interesting and informative. For example, the phenomenon of birds flocking or fish schooling can be described in three relatively simple mathematical equations. (see http://www.red3d.com/cwr/boids/ ), demonstrating that simple rules can result in complex behavior. (We err when we go on to conclude that complex behavior always results from simple rules or that we can impose simple rules on a complex system and have completely predictable results.) More recently, qualitative approached have been used, particularly in the context of the increasing popularity of “mixed methods.” A part of the stimulus to the use of qualitative methods is the desire to gain a richer picture of the experience of complexity.  We experience complexity in the world and often depend on intuition and sensemaking. For my course in the Doctorate in Management Program at the Weatherhead School of Management, on managing in complex systems I have felt the need to bridge academic and experiential complexity. Scholarly complexity may constitute that bridge.  I defined scholarly complexity as the conscious and systematic application of principles (regardless of their origin) that underlie complex systems to problems of practice in the real world – praxis. This frame of reference is a different way of looking at things and thus it involves a “complexity lens.”  In Part 2, I will describe the development of a complexity lens.

References:

  • Mitchell M (2009) Complexity: A Guided Tour. Oxford University Press, Oxford UK.
  • Byrne D, Callaghan G. (2014) Complexity Theory and the Social Sciences: The state of the art. Routledge, New York.
  • Boulton JG, Allen PM, Bowman (2015) Embracing Complexity: Strategic Perspectives for an Age of Turbulence. Oxford University Press, Oxford UK.
  • Beautement P. and Broenner C. (2011) Complexity Demystified, Triarchy Press. Axminster, UK.
  • Boisot, M. H., & McKelvey, B. (2010). Integrating modernist and postmodernist perspectives on organizations: A complexity science bridge. Academy of Management Review, 35(3), 415-433.
  • Geyer R., Cairney P. (20016) Handbook on Complexity and Public Policy. Edward Elgar Publishing, Cheltenham, UK.
  • Manson S. (2001) Simplifying complexity: a review of complexity theory. Geoforum 32:405-414.
  • Morin, E. (2007) Restricted Complexity, General Complexity, in: C. Gershenson, D. Aerts & B. Edmonds (eds) Worldviews, Science and Us, Philosophy and Complexity (London, World Scientific) pp. 5–29.
  • Richardson KA. (2008) Managing complex organizations: complexity thinking and the science and art of management. E:CO 10:13-26.
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