Learn More about Systems Science

I have made much mention of Systems Science in my recent articles. If you would like to learn more on this topic, then I recommend following Shingai Thornton’s blog at:

Shingai is a member of the International Society for the Systems Sciences (ISSS) and will write about the topic on a weekly basis. Each article takes about 5 to 10 minutes to read.

Initially, they will focus on making some of the core concepts in George
Mobus’ Principles of Systems Science textbook easily accessible to a
broader audience who might not have time to read the book.

Shingai is an aspiring systems scientist looking for critical feedback on his writing, and collaborations around the application of systems science to issues in the social sciences. He is receiving advice from George and other members of the ISSS education committee and together they are also developing an online course based on the book.

g. How to Gain Understanding

How to Gain Understanding


People understand the world through pattern recognition. Recurring patterns of events attract our attention, we remember them, attach meaning to them, and later use them as an aid to predicting the world. This trait has evolved to help our survival and the propagation of our genome. Non-recurring events are of lesser interest as they do not permit prediction. We are, therefore, less likely to remember and attach meaning to them.

Causality as a basis

Such recurring patterns of events have their basis in causality. It is likely that our perception of the latter has a hereditary basis. Certainly, other animals seem to understand causality, as evidenced by Pavlov’s famous behavioural experiments. Also, we have probably all experienced a young child repeating the question “why?”. This is probably him or her exercising hereditary skills in the recognition of causality.


Noticing these patterns is highly tentative at first. We merely notice similarities between events and feel an intangible sense of order. We do not have the words to describe what we notice, and it is not integrated into our general worldview. However, as our brains absorb the new information and make the necessary connections our understanding grows, and we can find words to communicate the insights. A general rule forms that we can use predictively. Unfortunately, this can be a slow process often involving several nights of good sleep and some research into the topic. This is effectively the same as the creative process of saturation, incubation, inspiration, and verification described in an earlier article, but with saturation replaced by experience.

We can also seek the fundamental origins of the recurring patterns that we observe. For example, the very concept of causality was discovered in this way. Patterns were recognised and causality was recognised as another pattern within them.


When we seek meaning we are essentially attempting to understand a pattern that describes the universe in its entirety. Unfortunately, however, pattern recognition is limited by our cognitive abilities. The principle of darkness applies, and our minds are simply not complex enough to model such a pattern. We can only recognise relatively simple ones such as causal relationships and feedback loops, and even those with difficulty. If there is any meaning to the universe, then it is certainly beyond our ability to perceive it. It would be more sensible to recognise this, rather than invent simplistic or mystical explanations. In practice, we must satisfy ourselves with understanding small parts of the world around us. For example, the purpose of this blog, is to convey an understanding of human nature and society.


As explained above, to understand a recurring pattern, it must be integrated into our general worldview. Obviously, if our worldview is a mystical or religious one, then we may give those patterns an explanation of that type. On the other hand, we will give the patterns a scientific explanation if our worldview is of that nature.


The process of predicting events and acting proactively is known in systems science as feedforward. This term is also used in personnel management to describe the training of staff to meet future business needs. The term feedforward suggests that it is the negative of feedback. However, this is only so in the sense that feedback is reactive to past events, whilst feedforward is predictive of future events. Feedforward relies on a knowledge of causal patterns. It is, therefore, a feature of agents or of systems created by agents.

How to Use this Process

We can reverse this recognition process. This involves designing a causal pattern and then looking for it in the world around us. Another approach is to generalise theories from specialised fields into general causal patterns. Once a pattern, for example the replication of information, has been created, we can then look for manifestations of it in the real world. In this way we may, for example, notice cellular division, the viral spread of misinformation on the internet, and so on. As explained in the previous article, there are many ways in which information can be altered during replication. So, two copies of the same information can contain contradictions. This in turn can lead to competition regarding which is correct, and, as will be described in a future article, to conflict. From this model it is possible to suggest reasons for real world events such as conflicts between closely related religious factions, etc.

In different fields and specialities, different words are often used for similar concepts. This tends to obscure similarities between the causal processes involved. However, once we have a pattern in mind, its recognition in the real world or in another field of expertise becomes much easier.