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.
Conversation
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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My first job out of college was working at a central bank.
There was a fantasy sports competition in the office.
One guy absolutely destroyed us all.
I asked him how he did it. He basically explained that most people were thinking of one most probable narrative.
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He said that there are multiple possible narratives, and created his strategy to win under each narrative.
That guy is now one of the people tasked with steering a nation's economy.
It gives me comfort that he was so far ahead of us, and could explain how he did it so clearly.
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