A Framework for Understanding and Achieving Sustainability of Complex Systems

This paper takes a systems approach to outlining a framework for the sustainability of complex systems. Complex systems have one or more functions that strongly interact with their environments, or the supra-system in which they are embedded. The success of the system in interacting with its environment over an extended time frame depends on that system’s ability to regulate its activities, both internal and external so as to remain ‘fit’. The concept of fitness derives directly from the evolutionary theory of phenotypic traits and capabilities (behaviours) being selected for or against by the environment of the system. But it is generalized beyond the standard neo-Darwinian biological process. The roles of adaptivity and evolvability and the mechanisms of a hierarchical cybernetic governance subsystem in maintaining these are advanced as necessary conditions for achieving sustainability in all types of complex systems. An operational definition of sustainability is advanced along with a set of necessary conditions that must obtain in order for complex systems to achieve it. Several systemic dysfunctional conditions are explored to show how complex systems fail to achieve sustainability by failure of the hierarchical cybernetic governance subsystem. Examples from several natural and human-built systems are used to demonstrate these conditions.Clarification of the meaning of complexity across a spectrum of system types is given. A definition of complexity based on hierarchical levels of organization is given to ground the discussion of the hierarchical cybernetic governance subsystem and justify its necessity to achieve and maintain stable dynamics in unstable environments. The purposes and uses of this framework are discussed and examples provided. A brief description of the use of systems analysis to explore and discover functional and dysfunctional subsystems within the hierarchical cybernetic governance subsystem and how this might provide insights for the design of better performing subsystems is also provided. The paper concludes with a projection of the benefits of applying this methodology to the governance of the human social system (HSS)