This law states that anything which aims to be a ‘regulator’ of a system needs to have at least as much variety as that system. In order to understand what that means, we need to get a short way into the theory of cybernetics. But for the meantime, for a sort of high-level metaphorical understanding, * think about how you steer various kinds of vehicles. A train can really only go forwards and backwards, so it only needs a single handle. A car can make turns, so its control system requires a steering wheel to represent the added dimension. And an aeroplane needs a joystick rather than a steering wheel, because it can make two kinds of turns. Let’s see where cyberneticians took this idea.

Which to be honest, is often all you really need in these contexts. The whole damn thing* in cybernetics is made of newspapers and high-level analogies. This isn’t computer science, where you can point to the states, bits and circuits on a piece of silicon.

Everything is driven by Ashby’s law of requisite variety: a given system has the potential to achieve stability only if every source of variability from the environment is matched by an equal or greater source of variety in the regulatory system.

This sort of decision is fundamental to the cybernetic analysis of systems; you are always attenuating variety in some way or other unless you are describing a system that consists of everything in the universe.

The first part of the model is System I, or operations, the bit of the organisation that is involved in making change in the real world. It’s a part of the system that could, in principle, be turned into an independent organisation.

A maximising system involves defining an objective function, and throwing away all the other information. Sooner or later, the environment is going to change, and something which isn’t in the information set any more is going to lead the system into destruction.

Consequently,

Every decision-making system set up as a maximiser needs to have a higher-

Level system watching over it.