"Stop dissing Bayes, it's a valuable tool if wielded properly. Just look at the difference between P(you're a blowhard) and P(you're a blowhard | you'd readily nuke your blog sooner than discuss it with the ethics board)"
(https://twitter.com/grkraml/status/1276911740526178305)

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IMO the issue with most people using Bayes is that they use it to draw attention away from the assumptions they make.

Example:

I want to give you the probability that you are an idiot, given that you are a rationalist, P(A|B).

This probability equals P(B|A) * P(A) / P(B), the probability that you are a rationalist given that you are an idiot times the probability that you are an idiot divided by the probability that you are a rationalist.

I’ve now turned a rhetorical question (the usually unserious probability that you are an idiot | rationalist) into a “scientific” looking problem which relies on three additional unknowns (P(B|A), P(B), and P(A)) that I’ll probably fill in with guesswork (or uncertain/inaccurate data from a pdf I found) if I’m your average Twitter intellectual. But since we get a nice “scientific” looking result, we can ignore that it was based on bunk to begin with.

Also, god forbid you ask them about the confidence intervals of their data and their conclusion.

Ive always viewed it as cool math, weird prior percents.

It’s brought up in Bostrom’s book, and it made a good case in that whole AI threat area.

But there is the Bo Winegard tweet:

[removed]

Bayes as done by statisticians: good shit if done well

Bayes as done by anybody else: what the fuck this is a statistical thing, are you going to do fucking Gibbs sampling in your head?