IN EASY WORDS - CSH

Complexity in easy words


Complex systems are everywhere. Until very recently we were not able to understand or properly control them. Complexity research is about to change that.

The puzzles of the (living) world


From ants and bees to human states, from earth and seas to economies – complex systems are all around us. What could be more natural than trying to understand them? Complexity science deals with questions that puzzled and challenged humankind since the beginning of time. They used to be unsolvable. Step by step we do better.

What are complex systems?

 

A research field that carries the word “complex” in its name is sometimes a bit hard to communicate. The most heard reaction is, “Huh, that sounds complicated!” – and the attention is gone.

 

So let’s start from a different angle. Let’s focus on the world of living beings – that is, on the world. Take a rainforest, a fish swarm or an ant state; a megacity that works as by a wonder; the weather & climate or the human brain. Think about population growth, a pandemic, the internet or financial markets – all part of the living insofar as they are man-made and -driven … These and hundreds of systems around us, in us, with us or run by us have one in common: they are complex systems.

 

That means, they are unlike dead things. Machines for instance: When you turn the gear wheel of a clock you know exactly what will happen next. But when we take action in a complex system we have a hard time to exactly predict the consequences and effects of your deeds.

 

Why is that?

 

To use the unbeloved no-go word: They simply are too complicated for the narrow human brain. We can’t look through thousands of links and feedback loops, keep track of million interconnected and interdependent parts in networks that, to make things worse, aren’t stable but constantly influencing each other in endless actions, re-actions and re-reactions.

Our ancestors answer to complexity was reductionism

 

Of course the homo sapiens, inventive species that it is, developed ways to deal with what it couldn’t understand. Some were (and still some are) believers: accepted and explained the incomprehensible as will of a supernatural power.

 

The more scientific minded broke down the wholes to parts and studied the pieces one by one: the heart; the blood; the eye. The roots; the leaves; the soil. Single chemicals or single economies (as function of rationally acting agents; we had to learn the hard way that humans aren’t rational at all).

 

This way of thinking, famously named “reductionist”, made us the most powerful species on the planet.

 

We shape the Earth in Man’s own likeness; this “progress” replaced the ever silent gods.

Complex systems never forget

 

What we start to realize–or have to learn–now is that complex systems don’t forget. For a long while they might forgive: We can treat them badly (or all too good), pollute, damage, change them by adding or removing parts, and yet won’t notice much of a difference. Complexity researcher found out that robustness and resilience are typical properties of complex systems: They might rumble here and there, change a little, repair some damages, adapt to others, but overall remain in a stable state.

 

Yet when the changes go on and on; when too much is removed from or added to a system; when only one little part of it is stressed a tic too much – the system reaches a “point of no return”. Like water that turns into ice when a certain temperature is reached it will change: rapidly, irreversibly, unstoppable.

 

This is the point where stock markets crash, where traffic jams, power grits break down, ecosystems collapse, patients die from organ failure, revolutions start, the climate runs riot. Once this point – called “singularity” by complexity scientists – is reached we can’t do much to influence or even stop the transformation. It will just happen until the system has reached a new–and very different–stable state.

 

 

That is why it is so important to understand how complex systems work.

 

That is why we need complexity science.