Filtered for water in history (22 Jan., 2018, at Interconnected) – Stafford Beer’s T- U- and V-machines and the factory managed by a pond

 

Source: Filtered for water in history (22 Jan., 2018, at Interconnected)

 

4.

Stafford Beer was the cyberneticist and business management pioneer who, in the early 1970s, built Project Cybersyn for the revolutionary government of Chile. Command economy meets socialist proto-internet.

In the early 1960s, he was running a more esoteric experiment, in pursuit of his desire to build an automated factory.

From historian Andrew Pickering’s essay, The Science of the Unknowable: Stafford Beer’s Cybernetic Informatics:

The T- and V-machines are what we would now call neural nets: the T-machine collects data on the state of the factory and its environment and translates them into meaningful form; the V-machine reverses the operation, issuing com- mands for action in the spaces of buying, production, and selling. Between the T- and V-machines lies the U-machine — the homeostat, or artificial brain — which seeks to find and maintain a balance between the inner and outer conditions of the firm

The U-machine.

By the way,

The cybernetic factory was not pure theory. By 1960 Beer had at least simulated a cybernetic factory at Templeborough Rolling Mills, a subsidiary of his employer, United Steel

It is a core tenet of (early) cybernetics that sufficiently complex learning systems are somewhat equivalent, whether they are made of flesh and blood, or vacuum tubes. It is this tenet which allowed the audicity of the cyberneticists to consider building “intelligent” machines, or to model the brain as a network of moving information.

And sure enough, when I went to the library to consult Beer’s collected papers, How Many Grapes Went into the Wine: Stafford Beer on the Art and Science of Holistic Management, Beer discusses the search for his ideal U-machine:

a self-organizing system need not have its circuitry designed in detail — otherwise what virtue is there in the self-organizing capability? Furthermore, if systems of this kind are to be used for amplifying intelligence, a fixed circuitry is a liability. Instead we seek a fabric that is inherently self-organizing, on which to superimpose (as a signal on a carrier wave) the particular cybernetic functions that we seek to model

And he continues:

Dr Gilbert, who had been trying to improve the Euglena cultures, suggested a potent thought. Why not use an entire ecological system, such as a pond?

So Stafford Beer captures a woodland pond, and attempts to train it to run a factory:

Accordingly, over the past year, I have been conducting experiments with a large tank or pond. The contents of the tank were randomly sampled from ponds in Derbyshire and Surrey. Currently there are a few of the usual creatures visible to the naked eye (Hydra, Cyclops, Daphnia, and a leech); microscopically there is the expected multitude of micro-organisms. In this tank are suspended four lights, the intensities of which can be varied to fine limits. At other points are suspended photocells with amplifying circuits which give them high sensitivity.

The intention was to communicate information about the factory into the pond via optical couplings. Earlier attempts, reported by Pickering, included attempts to induce small organisms — Daphnia collected from a local pond –to ingest iron filings so that input and output couplings to them could be achieved via magnetic fields.

The state of this research at the moment is that I tinker with this tank from time to time in the middle of the night.

I have this picture of Beer, in his slippers in his basement, trying to figure out not only how to speak to this tank of water and algae in its own language, but attempting to put it through business school.

What would be the management style of such a factory foreman? Risk averse? A deep sympathy with the principles of sustainability and the circular economy? (Given it sits in a closed-system tank.)

Our modern efforts into machine learning and artificial intelligence have a familiar feel: we place the neural network at the heart of the system… and just turn it on. And although we can’t tell how the neural network recognises a face or optimises a system, we can tell that they have some natural politics: AIs are unable – or unwilling – to correct for their implicit racism and sexism.

What is the umwelt of a pond? What is the umwelt of an AI?

Uber’s marketplace and Facebook’s newsfeed are run by captured artificial intelligences — unreasonably efficient optimisers, blind to human feelings, natural free market libertarians; a warp core of tremendous ability and held only just in check. We don’t know how these things make their decisions, but we are beginning to see the biases in their actions.

Obviously Stafford Beer’s experiments came to nothing: the factories of China are not run by captured, semi-sentient woodland ponds.

Or. Who knows. Maybe we should put one in charge of Facebook.