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Skip to 0 minutes and 10 seconds Complex systems are a set of interacting elements, individuals also responding to the environment without full central control. In social complex systems, the elements are individuals and such systems cannot be described in full detail centrally. In this lecture, I discuss some common characteristics of complex systems. First of all, emergent behaviour and spontaneous order. Emergent behaviour means that the whole is more than the sum of its parts. The behaviour of a complex system cannot simply be derived from adding up the behaviour of the individuals. A spontaneous order forms from the interaction of individuals following relatively simple rules. Think about a colony of ants. Think about a flock of birds.

Skip to 1 minute and 9 seconds Predictability in detail is impossible in social complex systems. Recall that it is impossible to describe the system in full detail. And that implies it is even more impossible to predict the cause of the system over time. But patterns can be described and analysed and their formation can be predicted. Let’s take the example of a soccer game. What can be known? We know the structure of the game. If somebody would tell you that a result of a soccer game is 43 to 42, you would know that this is probably not a soccer game. So we know the structure, but what cannot be known? We cannot know in full detail what will happen from minute to minute in a particular game.

Skip to 2 minutes and 1 second Let’s take the example of business cycles. What can be known? We know that an economy shows fluctuations over time, that indeed there is cyclical behaviour in the economy. We can know this pattern and structure. What cannot be known? You cannot know exactly from minute to minute or even from month to month how the business cycle will develop and then a turning point will come. Let’s take the example of financial stability, of financial instability and crisis, which will be discussed extensively at the end of this course. But here something similar can be said. We can know the structure of financial instability, that an economy can be prone to periods of instability.

Skip to 2 minutes and 47 seconds But you cannot know the exact timing of the turning point in advance. Let’s also look at the example of the Industrial Revolution. What can be known? Again we can know the structure, the pattern of a take off in industrial development. But again, what cannot be known is the exact script of that process. So it’s in history, like Mark Twain is told to have said, “History doesn’t repeat itself, but it does rhyme. There’s a certain pattern.” This example of the Industrial Revolution will come back in a lecture later in this course on history. Emergent behaviour, as a general principal, we’ll also discuss more extensively in one of the next week of the course.

Skip to 3 minutes and 38 seconds And will be shown also in other parts of this course. Let me turn to another common characteristic of complex systems, and that’s the so-called “small world principal.” The small both principal. Many complex systems form a highly interconnected network, and there are only a limited number of links between any person or any elements in that network and any other person in that network. There’s that famous example of the belief that only five or six steps are between any person in the globalised world. And we will come back to this issue in the lecture on that work theory. In this lecture, we have discussed emergent behaviour, spontaneous order and patterns and the small world principal as some common characteristics of complex systems.

Common characteristics of complex systems 1

This lecture comes back to complex systems in general and some characteristics they have in common.

Specifically, it introduces the notions of emergence and self-organisation. Furthermore, it discusses the possibilities and limitations of prediction in complex systems. Finally, it talks about the small-world principle. That is, the principle that we are all just separated by a few connections from each other.

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Decision Making in a Complex and Uncertain World

University of Groningen

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