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c. Further Principles of General Systems Theory

Further Principles of General Systems Theory

I will describe General Systems Theory in more detail in the next few articles, and then provide a systems based model which can be used to understand human society, how it works, and why it sometimes fails. This model uses the principles described below.

Near Decomposability. Many natural and artificial systems are structured hierarchically, and their components can be seen as occupying levels. At the highest level is the system in its entirety. Its components occupy lower levels. As we move down through the levels we encounter ever more, smaller, and less complex components. The rates of interaction between components at one level tend to be quicker than those at the level above. The most obvious example of this is the speed with which people make decisions. An individual can make decisions relatively quickly, but the rate steadily slows as we move up the hierarchy through small groups, organisations, and nations, to global society.

Sub-optimisation. This principle recognises that a focus on optimising the performance of one component of a system can lead to greater inefficiency in the system as a whole. Rather the whole system must be optimised if it is to perform at maximum efficiency. Its components must sometimes operate sub-optimally.

Darkness. This principle states that no system can be known completely. The best representation of a complex system is the system itself. Any other representation will contain errors. Thus, the components of a system only react to the inputs they receive, and cannot “know” the behaviour of the system as a whole. For the latter to be possible then the complexity of the whole system would need to be present in the component. The expression “black box” is used to describe a system or component whose internal processes are unknown, and “white box” to describe one whose internal processes are known. Most systems are, of course, “grey boxes”.

An interesting question arises from the principles of near composability and darkness. As explained in previous articles, human beings are motivated by needs and contra-needs. The question is, of course, whether groups of individuals, species, and ecosystems also have needs and contra-needs which differ from their individual members. Are reduced birth rates, for example, a natural species response to population pressures? If so, then near decomposability implies that, because groups, species, and ecosystems are more complex systems than single individuals, the processes which satisfy those needs will proceed more slowly. Darkness implies that as individuals we would be unable to “know” the processes involved, although as a society we might.

Equifinality. The processes in a system can, but do not necessarily, have an equilibrium point, i.e., a point at which the system normally operates. If, for any reason, the processes are displaced from it, then they will subsequently alter to approach that point once more. This characteristic is known as homeostasis. Thus, a given end state can be reached from many initial states, a feature known as equifinality. For example, if a child’s swing is displaced from the vertical and released, then, after swinging to and fro for a while, it will eventually return to the vertical.

Multifinality. It is possible for the processes in a system to have more than one stable point. If a process is displaced a little from one of them, it may ultimately return. However, if it is displaced too far, then it may subsequently approach another equilibrium point. This is a feature of natural ecosystems. If they are damaged in some way, they will ultimately return to a stable state. However, this state will often differ from the earlier, damaged, original.

Dynamic Equilibrium. This principle is like that of equifinality but applies to rates of change in systems. Some systems are dynamic and have a stable rate of change. If displaced from that rate of change for any reason, they will ultimately return to it. This is known as homeorhesis, a term derived from the Greek for “similar flow”. Again, a dynamic system may have several stable rates of change.

Relaxation Time. Relaxation means the return of a disturbed system to equilibrium. The time it takes to do so is known as the relaxation time.

Circular Causality or Feedback. Feedback occurs when the outputs of a system are routed back as inputs, either directly or via other systems. Thus, a chain of cause and effect is created in the form of a circuit or loop. The American psychologist Karl Weick explained the operation of systems in terms of positive and negative feedback loops. Systems can change autonomously between stable and unstable states depending on the dominant form of feedback. Feedback is, therefore, the basis of self-maintaining systems which will be discussed in the next article.

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