The evolutionary complexity of social and economic systems: The inevitability of uncertainty and surprise

Abstract

Social systems are evolving, multi-scale, spatio-temporal structures with emergent functions, needs and capabilities. One sensible definition of an ‘extreme’ event would be one that led to some qualitative, structural change in the system, as it went beyond the current ‘control limits’ of the system. Indeed, we can view any current structure and organization that characterize a system as being forged out of the past events and crises that led to change and innovation. Each individual, group, firm, corporation, shareholder and observer experience ‘path-dependent learning’, whereby current learning is conditional by the events and decisions taken in the past. In reality, the ‘new’ system or structure that comes into being at a given time, although initially seen as a successful response to some past problem, will move into an unknowable future that will necessarily end in some new crisis, the emergence of some unexpected new factors, effects or implications that will have to be dealt with. A simple probabilistic model of event dynamics is presented showing that the discussions of power laws and self-organized criticality assume a stationary situation and the probability of given events. We contrast this with examples from human systems that are about qualitative, structural change and path-dependent learning. The first example involves the handling of severe motorway traffic accidents and the second describes the evolution of supply chains by trial and error, as new practices are adopted or rejected in a changing competitive economic environment. Social and economic systems must evolve, and will do so through the occurrence of seemingly ‘extreme’ events, requiring adaptation and change. The important lesson therefore is to accept that there will be always a potential for unexpected and surprising events and that we need to build systems that are robust and resilient to their occurrence.