(2023-05-03) Davies The Valve Amplifier Of History
Dan Davies: the valve amplifier of history. I recently advanced the following sketch of an argument, claiming to “kind-of-sort-of believe it”: ((2023-04-05) Davies History Is The Bygone Which Wont Stay Bygone)
- 1. In order to learn the lessons from history, you have to correctly choose which historical example is relevant to the current situation.
- 2. You then have to correctly generalise from the historical example to extract the underlying principles which form the lesson from history.
- 3. And then you have to correctly apply those principles to the current situation.
- 4. All of which seems much more difficult than just knuckling down and solving your own problem, without messing around hoping that reading stories about the past will help.
Smart readers spotted immediately that I was being dumb and annoying on purpose; it took me a bit longer to realise. In fact, step 4 is wrong
The trick here is to realise that “recognising that an analogy is no good” is a relatively quick cognitive operation.
Any kind of problem solving is based on making mental models of the problem
Usually, disanalogies are quick to spot
Creating a mental model from scratch is a very expensive cognitive operation, though.
So, if you have a supply of previously existing mental models, it might be a very good strategy to just start going through them one by one
But where might you get a large supply of ready made mental models to go through in this way?
the constraint that they’re stories about things that actually did happen once should exercise some kind of rudimentary quality control on the library of candidate solutions.
These are some big ideas in cybernetics.
“Regulation by veto” is one of the most important ways in which complex systems achieve stability;
It's also an example of “variety amplification” (where the word “variety” is, in context, synonymous with the quantity that gets named “information” in information theory). (Law Of Requisite Variety)
the regulation-by-veto trick works by taking a very large source of environmental variability, and then shaping it with a filter that’s easier to apply.
someone who is personally quite dumb can still make good decisions as long as they’re capable of learning from their mistakes.
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