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Cybernetics

Cybernetics

Norbert Wiener
1948
T2 212 pages · about 3h 32m to read Open Librarygoodreads

Summary

Wiener, a mathematician at MIT, published this in 1948 and created a field. The subtitle states its scope: control and communication in the animal and the machine.

The unifying claim is that control and communication in machines, in living organisms and in social organisations obey the same mathematical principles, and that these principles centre on feedback. A system that measures the difference between its actual state and a target and acts to reduce that difference is performing the same operation whether it is a thermostat, a servomechanism aiming a gun, a person reaching for an object, or an organisation adjusting to conditions. Wiener developed this from wartime work on anti-aircraft fire control, where the problem was predicting an aircraft's future position from its observed track.

The technical content covers time series and prediction, the statistical filtering that bears his name, the treatment of information as a measurable quantity related to entropy, developed alongside Shannon's work, the mathematics of feedback and the conditions under which a feedback system becomes unstable and oscillates, and the analogy between nervous systems and computing machines.

Wiener also drew social conclusions. He argued that automation would displace routine human labour on a large scale and that societies should prepare for it, and he warned against applying the machinery to human beings without regard for consequences. He wrote about this at more length in The Human Use of Human Beings.

The book is mathematically demanding and the exposition is disorganised, moving between rigorous derivation and speculation. Cybernetics as a named field faded, with its contributions absorbed into control theory, information theory, computer science, systems biology and management science. The framework's influence is greater than its current visibility, and the treatment of feedback and instability remains directly applicable.

Key takeaways 7

  1. Control in machines, organisms and organisations follows the same mathematical principles centred on feedback.
  2. A system that measures the difference between its state and a target and acts to reduce it performs the same operation regardless of what it is made of.
  3. Feedback systems become unstable and oscillate when the correction is too large or arrives too late.
  4. Information can be treated as a measurable quantity related to entropy rather than as an informal concept.
  5. Prediction from a noisy observed signal is a statistical filtering problem with a determinate optimal solution.
  6. Automation would displace routine human labour on a large scale, which Wiener argued in 1948 that societies should prepare for.
  7. The analogy between nervous systems and computing machines is structural rather than metaphorical, because both process signals through switching elements.

Who should read it

Readers who want the origin of feedback and control thinking, which underlies systems analysis in engineering, biology, economics and management.

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Peter M. Senge · 1990

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Where it sits in the reference 2

Mental models
Mental models

Topics

ScienceMathematics and StatisticsTechnology and ComputingComplexity and systems scienceAI and machine learningPopular mathematics, history and puzzles