2023 Q4 | Edition 4 | Article 1
Chaos theory is actually a theory about finding order, while recognising the ambition in aiming for an ordered state.
When we are young and our world revolves around being at home and going to school or weekly clubs, order may seem the norm. This view is fortified by everything we learn at school. The things we are told that we need to learn and be judged by revolve around predictability and order. There are school rules that must be learnt and adhered to, laws of science that we are told never fail, there is the finality of only one correct answer in any test, and the absolute authority of the school bell in structuring the day. Since before the teachers were even born, though, science has had a very different view of the world. It is mostly characterised by chaos.
Chaos is not, as it might sound, the absence of rules. Beneath any seemingly chaotic science system there is a set of non-random structures determining what will happen next. The main problem is that they are largely invisible to us and considerable work is needed to accept that even the great Newton, with his theory of determinism, got it fundamentally wrong. Chaos was named when a researcher trying to predict weather patterns did what many of us do in maths classes. He rounded up a number to just 2 decimal points. The results went crazy. He ran the simulation again, with another miniscule change in one of the early figures - again - the results didn’t just deviate slightly. They went entirely off course. This led to the famous theory of the Butterfly Effect. If minute changes have so much impact on complex and dynamic systems, how do we even begin to trace problems back to their source?
The Calm in Chaos
From Chaos to Order
Chaos theory, the idea that in a dynamic and complex system small acts can have very large consequences, can be made to work in our favour. It means that, potentially at least, there are some small acts that could have a big and positive impact on the world around us. The challenge is to break down any problem into manageable parts and look for opportunities to make changes. There are four key ways to do this:
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Nomenclature - the process of naming things - is the route source of all intelligent thinking. Before an illness can be treated, it first needs to be recognised in a diagnosable form and named. The classification of species and chemical elements and even personality disorders has allowed people to distinguish unique conditions and then make sensible decisions around this newly named object. Naming and defining the different parts of your problem clearly is the first step to grasping the issue.
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To understand a complex system, you have to know what parts relate to the same system. A pond is a collection of plant, bacterial, insect and amphibian beings that belong in or directly around a pond. Seasonal buying patterns are about shopping data, but there are other things in that organising system, such as weather data and data on televised sports or road works, all of which might impact a decision to go out to the shops.
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Once the parts of an organising system have been identified, we need to begin to see how they effect each other. This might not always be easy. We might notice that there is an apparent relationship between ice cream sales and the murder rate. They both go up at approximately the same times of the year. The intermediary causal factor - warmer temperatures - might not yet have been uncovered. And so an open mind is needed.
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Smoking has a clear negative impact on health, and so the obvious thing is to ban all cigarette sales. Smokers lives will be saved, as will their family members, and doctors can spend their time on helping other patients. But what about the tobacco farmers in poor countries who cannot switch crops overnight? What about the police who will have to implement the new law, and the court system and perhaps even prisons who will be burdened with extra work if the ban is to be taken seriously? When we are able to identify all stakeholders, we start to make better sense of why things are as they are.
From apparent randomness to order
The process of breaking a problem down into its parts can go two ways.
On the one hand, chaos theory becomes a theory of order and if we can order it, we can organise it and start to control it.
On the hand, just because we can grasp the different parts of a system, it doesn’t mean that we can easily solve it. You are unlikely to grasp the entire system, and this is a fact worth bearing in mind constantly. You might be able to uncover some relationships amongst the parts of a system, but it’s still going to be challenging to control those relationships, and even harder to make practical sense out of what you have observed.
But there is still the hope that by controlling just one small parameter in the equation, we might be able to produce a completely different outcome.
A fly on the urinal!
When the managers at Schiphol Airport needed to reduce cleaning costs, they had to find a way to reduce spillage around the men’s urinals. Changing very personal behaviour is not easy. The solution? They drew a photo-realistic image of a fly right next to the drain. For the gents visiting the rest rooms, it was an irresistible invitation to get some in target practice in! Accuracy went up and cleaning bills went down, with no awkward conversations or rule setting to negotiate.
Sometimes out of chaos, a simple change can produce the order that we need.
The Hidden Problem
Data is almost always scrappy and incomplete. At any one time, we want to understand the big picture and the main trends, but so much is missing in what we can capture. Once we understand the data cycle, we can bring out the best in human and machine thinking.