Skip to content

Why Complexity necessitates trial and error but With a Plan

Why did complex systems theory become important? Because complex systems like changing climate and financial economy are increasingly influencing our dayly lives. What are complex systems, and how to deal with them?

To make things simple, let’s break the world apart in two. The Simple and the Complex. In the simple world, the position of the sun in twenty and two thousand years can be predicted. If we can do that, then predicting the weather is a matter of making better models, right?

No. Why not? There are too many variables influencing the weather. In predictions, variables have an increasing level of uncertainty. You just can’t precisely say what the temperature of the water will be in the middle of the Channel in ten days from now. And a slight difference in temperature might just cause a cloud to form. Small uncertainties can grow larger can make big differences. It’s not that we do not have enough information, it’s simply that we can not now because tiny differences in initial conditions can have huge impacts on the results.

Physicist Michael Berry found that when predicting the outcome of colliding billiard balls, after the ninth collision you would have to take into account the gravitati0nal force of each person standing next to the table, and at the 56th collision you would have to know the position of each particle in the universe to accurately predict the position of the balls. So even if the process is entirely deterministic (no random influences are interacting), it is sooner than later impossible to have enough data to predict the outcome of chaotic systems.

Let alone what would happen if something unpredictable like human behaviour enters the equation.

So we don’t predict or plan and just see what happens? This is where complex systems theory enters. It implies a different way of thinking. Even when you can not precisely predict, you can still come to grips with complex processes.

Complex systems show properties of life. Things grow and emerge out of them; one moment there’s just water vapor, the next moment there’s a cloud. Complex systems learn and show evolution. They show feedback and grow in cycles or iterations. One really interesting theory, by the late Gregory Bateson, rolls out a definition of mind from system theory.[1] The idea that mind could be made up of information, forming a layer of reality that does influence the material world but exists in its own domain seems very helpful and more like truth than the still prevalent idea that mind can always be reduced to physical properties (“no you don’t feel depressed, it’s just a chemical substance in your brains”).

How does this help in coping with complex systems like global climate and economy? First, be modest with predictions. Second, be generous with blueprints and proposals but incorporate learning cycles, feedback loops and tipping points. Acknowledge that change is a process, not a project. Use networks and stimulate and recognise self organisation.

And don’t use extensive planning with strict targets. Just look at this documentary by Adam Curtis to get an idea of where this has taken us. 

  1. [1]Bateson (1979)