An executive summary of complexity theory

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An executive summary of complexity theory

Johnson, N. (2007). Simply complexity: A clear guide to complexity theory. OneWorld Publications, Oxford.

Futurists are in the business of providing a structured vision of the future that includes variables, dynamics, processes, themes and values by which the future will unfold and how we can be successful getting there in our  journey along the way.

Every futurist I’ve encountered describes the increasing complexity of today’s world and the certainty that the complexity will only increase going forward. I thought it would be useful to summarize the best book I’ve found so far that describes complexity theory in a useful way.

Complexity theory is a discipline that ties together phenomenon like: traffic congestion, the collapse of financial markets, avalanches, terrorist attacks and networks, pandemic viruses and cancer.

There is understandably senses definition for a theory which proposes to manage the unmanageable, or cleanly defined the undefinable.  Neil Johnson offers the following working definition which is a reasonable start point for approaching this topic:

[complexity theory is ] “…the study of the phenomenon which emerged from a collection of interacting objects.” (Johnson, 2007, p.3)

The theory is especially concerned with groups of actors that are interacting by competing for resources.

It’s fair to ask of the theory of complexity: will it help us understand, predict and control complex situations?

Emergence is an important topic: it deals with behaviors and or qualities that arise without warning, without apparent central control and are properties of the entire system and environment and not of individual components. The wetness of water can be considered an emergent property or the flocking behavior of a large group of birds. Both have qualities and properties that cannot be found in individual agents.

The idea of emergence includes the idea of emergent design through adaptation to dynamic conditions. Consider the case of DNA versus intelligent design. Evolution by adaptive DNA is without apparent central control and develops without warning and usually in unpredictable ways with unforeseeable magnitudes of outcomes;  intelligent design takes the opposite position in every way: central control according to a pre-established plan that goes according to design with foreseeable and specified outcomes.

Johnson offers the following components and behaviors that seem to apply to most complex systems and situations.

Components:

  1. The system contains a collection of many interacting objects.
  2. The behavior of agents/objects is affected by memory or feedback.
  3. Objects/agents can adapt their strategies based on memory or feedback.
  4. Exists in an open system, affected by the environment.

Behaviors:

  1. the system appears to be alive.
  2. Filled with emergent phenomenon that are surprising and can be extreme.
  3. Absence of an invisible hand or central controller.
  4. There is a mix of orderly and disorderly behavior.
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