Something that I’m chewing on that I haven’t quite pinned down (or properly developed a view on): Bayesian thinking may well be the most effective way to think when faced with uncertainty, but Bayes’s Theorem may be the wrong way to teach it.
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This tweet brought to you by the observation that some of the most intuitive Bayesian thinkers I know don’t explicitly update using percentages.
Instead they seem to do something different. Many of them seem to generate multiple explanatory stories instead and hold them loosely.
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The end result might be a Bayesian updating process, but the internal machinery is very different.
Human brains don’t seem particularly well suited to calculating priors and percentages but they seem particularly well suited to generating explanatory narratives.
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Mathematically inclined people seem to enjoy talking about Bayes’ Theorem, and they seem to be able to explicitly calculate priors/percentages.
But I wonder if it’s the only way to get there. It seems to go against the grain of the mind (eww maths; yay stories).
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Thanks for the recommendation! Do you have specific episodes you recommend?
I’ll come back to you on episodes from ToKCast. In the meantime: bretthall.org/bayesian-epist
The relevant Naval podcast on this is:
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I‘ve no more criticisms of Bayes’ theorem than of Pythagoras’ theorem. But if a purported “geometry” says it uses the latter (alone!) to generate shapes not seen before, I’d have questions.
Anyways, I discuss “Bayesianism” here: youtu.be/DHLTBOJ5hoQ &
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