The example described in my previous post can be described graphically and, potentially, a mathematical or computer model can be created. A diagrammatic representation of the example is given in the figure below.
Figure 1. Causal diagram showing increasing complexity in Western society.
In this diagram, the coloured rectangles represent a society’s variable characteristics. These characteristics have numerical values that alter with time and can be related to one another mathematically. The variable characteristics interact causally as shown by the arrows, which point from cause to effect. In this diagram, all the arrows show the cause as being sufficient for the effect. If several sufficient causes impact on one effect, then their effect is cumulative. However, by joining arrows together after they have left their causes, it is possible to represent several necessary causes as, together, being sufficient for an effect.
The smaller rectangles describe the nature of the causal relationship. A small up arrow indicates an increase in the variable characteristic. A small down arrow indicates a decrease. The coloured background indicates whether the small arrow refers to the cause or to the effect. Small arrows are paired horizontally. In rectangle B, for example, an increase in the cause results in a decrease in the effect.
The diagram can be explained as follows.
A. As the number of established organisations increases, so too does the total number of inefficiencies. The reverse is also true.
B. As the number of inefficiencies decreases, the number of unattached individuals with unsatisfied needs increases. The reverse is also true.
I. The number of unattached individuals also increases as the population increases. The reverse is also true. Note that population growth is the number of people entering society due to births and immigration, less the number of people leaving it due to deaths and emigration. However, not all of the population is active.
C. As the number of inefficiencies increases, the number of trading opportunities for unattached individuals also increases. The reverse is also true.
D & E. As the number of trading opportunities and the number of unattached individuals increases, the number of goods and services that can reduce inefficiency in established organisations also increases. However, the reverse is not true. A decrease in the number of trading opportunities or a decrease in the number of unattached individuals has no effect.
F. As the number of goods and services provided increases, the number of inefficiencies decreases.
J. The number of inefficiencies also reduces because of efficiencies carried out by the organisations themselves, i.e., auto-efficiencies. The reverse is also true, and organisations can cause greater inefficiency in many ways.
G. As the number of goods and services provided increases, the satisfiers received in return also increase. The reverse is also true.
H. As the number of satisfiers received increases, the number of established organisations increases. The reverse is also true.
It can be seen from this diagram that the process is a positive feedback loop. With no constraints, the number of established organisations, and thus, the complexity of society can increase exponentially. However, the minor feedback loop BEF can have a damping effect if there is insufficient population growth.
There are many other examples that would benefit from the same approach. However, they may not be independent of this model, but rather may interact with and extend it. The more examples we consider, the more questions this will raise. If common questions arise from different examples, then this may be an indication of their significance. Answers to some of these common questions may be beneficial in all cases. However, it is also possible that they will be beneficial in some and harmful in others. This is not a bad thing, however, because it would prevent ill-considered decisions, and encourage us to seek optimal solutions.