Complex Adaptive Systems
I haven’t found any nice, succinct descriptions of Complex Adaptive Systems. The first time I came across the concept was in Appendix B of “Crossing the Quality Chasm”, a report on American health care published in 2001 by the Institute of Health. (ISBN 0-309-07280-8). Here’s their definition – “A complex adaptive system (CAS) is a collection of individual agents that have the freedom to act in ways that are not always predictable and whose actions are interconnected such that one agent’s actions changes the context for the other agents.” Although that’s not a particularly clear or easy definition, they go on to list a number of properties of such systems and this is where it gets interesting from the human perspective. If we consider ourselves using this concept of the CAS we can understand a lot about why we have certain experiences, and even more interestingly I believe, we can begin to develop a working model of a healthy, thriving person. Here are the properties -
Stands to reason that a CAS will be adaptive. What it means though is that we can change. Change the circumstances, the influences on, and conditions of, a life and the healthy person will adapt. They will cope. They will have resilience.
Although the outcomes of change are complex they come about on the basis of simple rules. Each building block, or element, or agent can be quite simple.
In linear systems a certain impact will always deliver the same effect. However, in nonlinear systems, there are always number of factors which continuously influence each other. Through feedback loops every element in the system dynamically influences all the other elements.
Non-linearity is responsible for the next two properties -
Novelty. A CAS is naturally continuously creative developing new ways of responding and coping, producing new behaviours previously unseen
Not predictable in detail
Because of non-linearity and emergence it is not possible to predict detailed outcomes. This has been described as the “butterfly effect” – small changes in the starting conditions of a system lead to large, unpredictable differences in outcomes. This is very important when thinking about prognosis – it might be possible to predict how things, statistically, might turn out, but it is impossible to predict accurately for this one person how things are going to go.
Through these mechanisms a CAS has a self-maintaining capability. When you think about the complexity of a human being you might wonder what holds it all together? What controls all the various elements and produces the co-ordinated behaviours? Is there some life-force, or some organ, some conductor of the orchestra, that keeps it altogether? Well, no. A CAS has inherent order. It’s the actual complexity of the system which allows the system to self co-ordinate.
Context and embeddedness
“No man is an island”. Systems all exist within, and in interaction with, other systems. This means that to understand any particular organism, for example, to understand any individual human being, you need to situate them in their environment, see them in their contexts and connections.
As an individual changes those changes impact on everything that individual is connected with, so as individuals grow, so do their environments.
In addition to these properties of a CAS there are other ones which are shared with all complex systems (whether adaptive or not)
The most widely known type of attractor is a “point attractor”. In astronomy a “Black Hole” is a good example. In your bath tub, the drain is one! A “point attractor” pulls everything towards itself. There are two other important attractor types. “loop attractors” – these are attractors with two points of equal power both of which exert their influence on their surroundings resulting in two alternating states which the system flip flops between. The other kind is the “chaos attractor” which doesn’t look like an attractor at all because everything around it is chaotic.
Far from equilibrium points
A complex system is not static. It does not constantly maintain the status quo by keeping everything in fine balance. Complex systems move towards instability by moving to what are termed far from equilibrium points.
At a far from equilibrium point the system acts as if it has a choice. It can go one way, or another. A bifurcator is like a crossroad.
At a far from equilibrium point the system can suddenly change its whole state. An example of this is boiling water. As you apply more heat the water molecules become more agitated and at the “boiling point” the liquid water changes state and becomes steam – a gas.
All of these phenomena are natural phenomena. Understanding them can help us to understand ourselves because we are complex adaptive systems.