Wednesday 12 February 2020

Brains and Institutions: Why Institutions need to be more Brain-like

I was grateful to Oleg for pointing out the double meaning in Beer’s Brain of the Firm last week: it wasn’t so much that there was a brain that could be unmasked in the viable institution; firms – institutions, universities, corporations, societies – were brains. Like brains, they are adaptive. Like brains they do things with information which we cannot quite fathom – except that we consider our concepts of “information processing” which we have developed into computer science – as a possible function of brains. But brains and firms are not computers. That we have considered that they are is one of our great mistakes of the modern age. It was believing this that led to the horrors of the 20th century.

So what is the message of Brain of the Firm? It is that firms, brains, universities, societies share a common topology. In the Brain of the Firm, Beer got as close as he could to articulating that topology. It was not a template. It was not a plan. It was not a recipe for effective organisation. It was not a framework for discussion. It was a topology. It was an expression of the territory within which distinctions are formed. Topology is a kind of geometry of the mind.

Universities are particularly interesting examples. Because they are made of brains, and because their work is meant to be the work of their constituent brains. Universities present an example of where the “brain-organisation” sometimes goes right, but more often goes wrong. Why does it go wrong? Because we draw our distinctions in the wrong way – most often believing the institution to be the “organisation chart” – which is always a recipe for disaster.

Governments and states are alternative examples. One of the things we talked about was the general antipathy to the big state. The apparent failure of the Corbyn project is a hangover from the general disbelief in the big state. Johnson’s message is a throwback to Thatcher’s message – ironically this time marshalling the support of those who Thatcher hurt the most. But really, this message – the disbelief in the big state – never went away. After Stalin’s Russia, there appeared nowhere for the big state to go. But ironically, Stalin’s Russia was really a small state masquerading as a big one.

Today the world is full of would-be Stalins. Individuals wanting to impose their brains on everyone else, wanting to diminish the power of every collective unless it suits themselves. The model is repeated from corporation to university to city to state. But in the end, it will not work except to destroy its own environment (which it is doing very effectively), and it will not work because the distinctions are drawn in the wrong place.

The real question we should ask ourselves is this: How do brains work and how should organisations work to emulate them? Technology almost certainly gives a glimpse.

If there is a key feature of Beer’s fundamental topology it is the difference between the inside and the outside of a distinction. I wonder if in fact Spencer-Brown wasn’t influenced in his mathematics by Beer. I suspect Beer had the insight of Spencer-Brown’s most powerful idea first.

If you want to maintain any distinction then you must have a metasystem. Why? Because all distinctions are essentially uncertain, and there must be a mechanism – there must be the other side of the Mobius strip – to maintain the coherence of the distinction.

What must the metasystem do? Well, one of the things it must do is negotiate the distinction of the inside with the environment. In essence it has to determine what belongs inside and what belongs outside and to maintain this boundary. If it doesn’t do this, then the distinction collapses. So there must be a process of engaging, probing and modelling the environment.

This is System 4

The other thing the metasystem must do is to manage the internal operations of the system – its own internal distinctions. This is System 3.

Then it must balance the balancing operation of System 4 and System 3 This is System 5.
So very quickly we arrive at this topology.

But this is the topology of a distinction, and within any topology there are further distinctions. The point is it unfolds a fractal structure. This ultimately is the fractal structure of the inside which must be balanced with what is perceived as the fractal structure of the outside.

The challenge is to operationalise this.

For many who pursued the VSM, the operationalisation ended up as a kind of consultancy – a way of talking to organisations to give them a bit more internal awareness. I guess this was fine -  and it created a bit of work of cybernetics people. But ultimately this was empty wasn’t it?

How do we do better?

We need to come back to brains and firms. Within the brain, we have very little knowledge of what happens – particularly as to what happens with information. Obviously there are ECG monitors and stuff but they simply attenuate whatever complex activity is going on into graphs that show some kind of snapshot of the dance that’s really taking place.

We can see much more of “information” if we look at communications. Then what do we see? We see massive amounts of redundancy in our communication. We see pattern infusing everything, catching the attention of analysts and clairvoyants. The clairvoyants are usually more value because they tune-in to something deeper.

The deeper problem lies in the way we are able to analyse and examine the patterns of communication. It’s not as if we are short of data – although there can always be more. It is more that we do stupid things with the data we collect. Typically this involves attenuating out most of it and using an attenuated dataset as an exercise to make stupid decisions.

It’s rather like a brain with dementia. Important parts of the processes of maintaining information flows throughout the whole organisation are damaged – in the institution’s case, by technology – and consequently the selection mechanism for adaptation is impaired. Consequently the poor individual afflicted with this, steps into the road without bothering to check the approaching double-decker bus.
Our institutions are doing a similar thing for a similar reason. Key parts of their information processing apparatus are impaired which means that the selection mechanism for their future adaptation isn’t working.

So what is a selection mechanism for future adaptation? It is precisely what Beer, influenced no doubt by Robert Rosen, called an “anticipatory system”. It is the system’s model of itself. Now a model of oneself in time must be a fractal.  The only way the future can be predicted is through its pattern of events being seen to be similar to the past.
That is not that actual events repeat (although of course they do), but it is that the pattern of relations between particular events tend to repeat.

But we need to understand fractals. They are not really two-dimensional pictures. They are three-dimensional pictures. Long before we knew about fractals we knew the concept from the hologram – that encoding of time and space into a 2-dimensional frame where the self-similarity of the frame was its key feature.

The reason why fractals are so important is that our approaches to information and measurement are essenatially 2-dimensional. Look at Shannon’s diagram to see this. The deep problem with 2-dimensionality is that it has no concept of “nothing”. In Shannon, any symbol exists against the constant background of a not-symbol, but we have no way of expressing the not-symbol.
True nothingness means making things disappear. It turns out that the only way we can make things disappear is by working in three dimensions. The fractal is an encoding of three dimensions in which “nothing” is written through like a stick of rock. Nothing is what makes the pattern.
All human behaviour in institutions is really about nothing. Or rather, it is about the attempt to grasp nothing from something. In the way that a piece of music eventually selects its ending – and silence – all our behaviour seeks a kind of resolution. Every conversation seeks a resolution. Every interminable meeting frustrates because its ending frustrates.

But if we want to see nothing, then we have to work with its encoded representation – the fractal.
Our mathematical approach to information – to computer information – can provide a glimpse of nothing. Indeed, our approaches to machine learning, which are beginning to show behaviour that is rather like conscious behaviour, are providing a glimpse – they too are fractal.
If we want to see nothing, then we need an encoding strategy whereby data is represented in a way where nothing might be analysed and considered.

If we want viable institutions, then we need viable individuals. If we want viable individuals then we need a way of encoding the communicative behaviour of individuals in a fractal which can reveal the underlying selection mechanism for optimal future development. It would not be a surprise if the optimal selection mechanism for individual development involved communication with other individuals. And it would not be a surprise if the optimal collective development of a group of individuals entailed the preservation of information between them.

What do we have? Monasticism?

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