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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For an entertaining example of this, check out ’s story of investing in a pachinko company.
Totally Bayesian in thinking style; totally not Bayes’ Theorem in execution.
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That's an astute observation. Holds for the intuitive thinkers I know, too (small sample).
Personally, I think of the percentages as a way to communicate the 'feels' of an uncertain position to another person.
But updating a position is story and feel-based, not arithmetic.
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The internal thinking is like a quantum superposition of possible future states
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I'm generally very explicit, but I don't understand how you can practically use Bayesian thinking in an explicit way.
Do people really try to assign percentages to events and literally update their priors?
Building stories and intuiting which is correct feels way more natural.
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