Why the idea of complex systems matters

The difference between complex systems and ordinary systems is that complex systems are fundamentally indeterministic. A while ago, Joe Firestone explained why to me using our current understanding of quantum mechanics. Paraphrasing, the key point was that:

complex systems are deterministic on a multiverse level, but indeterministic from the point of view of any single universe.

Unfortunately, to the layperson, it is common to conflate this kind of “complex system” with “extremely complicated deterministic systems”, and the confusion leads to many misconceptions and bad lines of argument.

I’ve focused primarily on a type of complex system in my study and application of Knowledge Management – complex adaptive systems (CAS). Any system involving humans is fundamentally a CAS, although the inverse proposition is not necessarily true.

Relying on cause and effect when dealing with and analysing complex systems is dangerous because a belief in deterministic causes and effects is the origin of the Command and Control management strategy. We believe we can achieve a particularly outcome “if we only had better tools to control them”. But we can’t!

Successfully dealing with complex systems means adopting a whole new toolkit that relies upon managing concepts like propensities and coherent outcomes. One of the major ideas within a CAS is the use of iterative decision execution cycles – PDCA, OODA, and the like. Another key concept is the idea of safe-fail experimentation to explore possible system outcomes in a recoverable manner.

(Cross-posted here after some editing from http://clubtroppo.com.au/2012/04/30/review-drift-into-failure/#comment-472475.)

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