The interdisciplinary body of knowledge known as Complexity Science has emerged over the past four decades to explore the characteristics of these complex and adaptive systems.
Complex adaptive systems (CAS) are all around us, in fact we are a complex adaptive systems ourselves, with our bodies made up of numerous parts, all interacting, influencing and responding to changes in the greater system, resulting in the overall level of our body’s health. Our telecommunications systems and stock markets are complex adaptive systems, as are rainforests, weather systems, and the internet. Each of these systems evolve in relationship to the larger environment in which it operates. To survive, the system as a whole must adapt to change.
Complex adaptive systems theory has taught us some valuable lessons about the nature and behavior of complex systems, which we can harness to our benefit.
Complex adaptive systems (CAS) are all around us, in fact we are a complex adaptive systems ourselves, with our bodies made up of numerous parts, all interacting, influencing and responding to changes in the greater system, resulting in the overall level of our body’s health. Our telecommunications systems and stock markets are complex adaptive systems, as are rainforests, weather systems, and the internet. Each of these systems evolve in relationship to the larger environment in which it operates. To survive, the system as a whole must adapt to change.
Complex adaptive systems theory has taught us some valuable lessons about the nature and behavior of complex systems, which we can harness to our benefit.
Sub optimal: A complex adaptive systems does not need to be perfect in order to thrive within its environment. It only has to be slightly better than its competitors and any excess energy expended is wasted.
Requisite Variety: The more robust the system, the greater the variety. In complex systems, ambiguity and paradox create new possibilities for the co-evolution of the system.
Connectivity: Agent relationships (connectivity) in a system is critical to the survival of the system. How agents connect and relate to one another creates the patterns from which evolutionary feedback is circulated.
Simple Rules: Complex adaptive systems are not complicated. The emerging patterns may have a rich variety, but the rules governing the function of the system are quite simple.
Iteration: Small changes in the initial starting conditions of the system can have large effects. The iterative process of agent/system/agent interaction can amplify the emergent outcome.
Requisite Variety: The more robust the system, the greater the variety. In complex systems, ambiguity and paradox create new possibilities for the co-evolution of the system.
Connectivity: Agent relationships (connectivity) in a system is critical to the survival of the system. How agents connect and relate to one another creates the patterns from which evolutionary feedback is circulated.
Simple Rules: Complex adaptive systems are not complicated. The emerging patterns may have a rich variety, but the rules governing the function of the system are quite simple.
Iteration: Small changes in the initial starting conditions of the system can have large effects. The iterative process of agent/system/agent interaction can amplify the emergent outcome.
There are three different types of system in which our society operates, and all have to be managed in different ways. Two are familiar to us, the ordered and chaotic systems, but the third, complex systems, have only recently received the attention they deserve:
Where we once enjoyed the stability of relatively small, stable and comparatively self contained communities with limited outside interaction, today our world is a vast, interconnected network of relationships which span cities, states, countries and continents. Our society has become a very complex system.
Within our increasingly networked social systems, our organisations, markets, and even individuals are in a state of constant evolution, as they accommodate the impact of new information, ideas, trends, fashions, fads, and behaviours. If an idea or trend successfully 'catches on', its influence can cascade across the system, as individuals influencing each other impact and subtly change the system, which in turn impacts the individuals in a virtuous cycle of feedback loops that continue until the system either adapts and evolves to a new steady state, or experiences catastrophic system failure.
Where we once enjoyed the stability of relatively small, stable and comparatively self contained communities with limited outside interaction, today our world is a vast, interconnected network of relationships which span cities, states, countries and continents. Our society has become a very complex system.
Within our increasingly networked social systems, our organisations, markets, and even individuals are in a state of constant evolution, as they accommodate the impact of new information, ideas, trends, fashions, fads, and behaviours. If an idea or trend successfully 'catches on', its influence can cascade across the system, as individuals influencing each other impact and subtly change the system, which in turn impacts the individuals in a virtuous cycle of feedback loops that continue until the system either adapts and evolves to a new steady state, or experiences catastrophic system failure.
A consequence of the new found understanding of complexity, is the need for a new paradigm in understanding the dynamics of our social, economic and natural environments. Complexity science disavows the reductionist worldview, where things could be understood by examining their parts in a linear, mechanistic way. In its place is a new worldview where nonlinear, dynamic, evolutionary development calls for a new way of thinking about, understanding and influencing the dynamics of complex systems, issues and emerging situations.
Unpredictability: the interactions of agents within the system are unknowable in advance, with unpredictable interactions creating the emergence of patterns which informs both the behaviour of the agents within the system and the behaviour of the system itself. Complex adaptive systems are therefore said to be emergent in nature.
Co-evolution: as agents interact, they change, affecting their surrounding environment. And as their environment changes, the agents evolve with it, in a co-evolutionary cycle, unless/until a steady state is reached.
Self Organising: Complex adaptive systems have no hierarchy of command and control. Constant re-organising to find environmental best-fit replaces hierarchy and top-level management.
"Fluffy Boundaries": A lack of rigid boundary conditions within a CAS make their exact composition impossible to determine. Within such "fluffy boundaries", it may be left to an observer to determine where the system's boundaries lie.
Co-evolution: as agents interact, they change, affecting their surrounding environment. And as their environment changes, the agents evolve with it, in a co-evolutionary cycle, unless/until a steady state is reached.
Self Organising: Complex adaptive systems have no hierarchy of command and control. Constant re-organising to find environmental best-fit replaces hierarchy and top-level management.
"Fluffy Boundaries": A lack of rigid boundary conditions within a CAS make their exact composition impossible to determine. Within such "fluffy boundaries", it may be left to an observer to determine where the system's boundaries lie.
What is Complexity?
Complex adaptive systems share the following attributes: