Strategies for Influencing Complex Adaptive Systems
Last modified: May 31, 2007
Most of the challenging problems we face arise in complex adaptive systems and larger systems containing complex adaptive systems. Such problems are daunting because of their high dimensionality and opaque underlying dynamics. How are we to even begin to unravel causes and effects, and indirect influences, and contingent factors that can trigger unexpected consequences? We will argue that the central issue to be addressed here is networked causality and that better techniques for mapping and analysing causal and influence networks are urgently needed. A program towards this end will be outlined, including a methodological framework for addressing complex problems. The framework employs multiple perspectives drawn from the theory of complex adaptive systems, and in its initial stages, aims to clarify the dynamics that are relevant to producing the problem. Intervention strategies are developed through a combination of harnessing the adaptive mechanisms that are identified in the dynamics, and if necessary, the creation of additional adaptive processes. In truly complex systems we know that detailed predictive control is not possible, but we argue that such intervention strategies can influence future outcomes if applied adaptively.