#systems theory

I know people on this site love "The purpose of a system is what it does" so here's where that comes from.

Cybernetics is the transdisciplinary study of control and feedback in systems. In other words, how systems stay in a stable state based on the inputs and feedback they receive. It is relevant to every branch of science and is the origin of the word Cyber. It was first defined by Norbert Weiner in 1943, and adapted for a business and organisational context by his student Stafford Beer in Brain of the Firm (1972).

Important concepts in cybernetics include: -“The purpose of a system is what it does” meaning that if a system is failing to meet its stated goals then that is a result of the current state of the system and it must be changed. -The idea of the “Black Box” meaning many systems are black boxes, too complicated to fully model, and instead should be evaluated by looking at their inputs and outputs, and how external and internal feedback influences them. -The Law of Requisite Variety: The idea that to control a system, the controller must have at least as much complexity of the system it is controlling. A car changes speed and steers, so it needs pedals and a wheel. A plane moves in three dimensions, so it needs a yoke and pedals to give it three dimensions of control. Management must have information complex enough to make informed decisions but not so complex it overwhelms them, and information can be amplified or attenuated to get to the level of variety needed in given situations. Management needs feedback from both the internal and external environment in a form they can quickly understand and react to, and the ability to give feedback to internal systems in an effective manner.

In Brain of the Firm, Beer defines the Viable Systems Model. This is a sort of a “Theory of everything” of management, and nearly every other management theory I have studied neatly fits inside it. It is based on how humans process information and learn. Put simply, an an organisational system will have five elements:

Operations: The people performing the actual functions of the system.

Co-Ordination: Managing resources and dealing with crisis

Tactics: Setting targets and pushing towards them.

Intelligence: Examining external environments and and possible futures to plan ahead

Ethos: Philosophy, Norms, and Beliefs.

Each role can be held by many or multiple people, based on what they actually do and not always job role. They must have communication systems between them that amplify or attenuate information based on the needs of the people. If any of these stop functioning the system will fail. Most interestingly, the system is considered a “Fractal” meaning it is the same at every scale. It can be true for a team, a department, a company, and an industry, all at once, with each Operations element containing an entire viable system inside it. I find nearly every theory I have looked at including Resource Based View, Dynamic Capabilities Theory, Stakeholder Theory, Sociotechnical Systems Theory and most others I studied at undergrad fit nearly inside this framework, and I think it is will be a useful tool to have in my toolbox in terms of setting measurements and examining feedbacks from different stakeholders, as well as scaling down as low as teams and scaling up to the level of trade associations. I have attached a diagram of the model from Wikipedia as it helped me understand the concept.

The EU AI Act is often perceived primarily as a regulatory challenge, as another layer of compliance requirements, documentation obligations, and control mechanisms that organisations must integrate into their existing processes. This perspective, however, remains incomplete. The deeper significance of the EU AI Act lies not only in the requirements it imposes on AI systems, but in the structural…

For example.

A Crawler HAS Agency BUT NO Authority

A Monsters/NPCs HAS NO Agency AND NO Authority

The System AI HAS NO Agency BUT Authority

SO

The Corporation HAS Agency AND Authority

And this is correct

At first

Until it isn’t.

Because none of it is prescriptive and says how it has to be.

Just how it is at the moment.

What It Means To Persist Through Time

Available on Amazon & IngramSpark

The answer, rather counterintuitively, is that they are durable because they are not optimised. An optimised design is one that has been tuned precisely as possible to its current conditions. Every component fits perfectly to its present demands. Nothing is wasted, nor is anything redundant. The system performs beautifully under exactly the conditions for which it was optimised.

What happens when the conditions change?

The more precisely a system is tuned to one environment, the greater the chance that it will fail catastrophically when that environment changes. Environments change all the time, so this is not a hypothetical concern. The climate changes, competitors arrive, the pH of the environment changes, a new virus turns up, food sources disappear, your host takes an antibiotic. The one thing you can say for sure about present conditions is that they will not last.