By what metric do you judge a reference class?

post by B Jacobs (Bob Jacobs) · 2020-06-15T18:34:18.262Z · LW · GW · 1 comment

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    1 NeilDullaghan
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The reference class problem is when you have a singular phenomena (e.g your friend Josh) and to extrapolate data and make predictions about this singular phenomena, you have to put it in a reference class of similar phenomena. The question becomes how you quantify similarity [LW · GW]. Everything has an indefinite number of proporties that could be used as the basis for selecting a reference class (Josh is male, likes jazz, is an animal, is born in Germany, has a freckle on his toe etc). You can almost always select a reference class in such a way that you get the results you want to see. So how do you judge a reference class?

EDIT: Put up a $100 bounty for anyone who can solve it before 2022 [LW(p) · GW(p)]

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answer by NeilDullaghan · 2021-12-29T14:18:59.055Z · LW(p) · GW(p)

I wrote a "how to" guide for picking a reference class here. Would be interested in any feedback from experienced forecasters. I haven't posted it because the example I work through is part of an upcoming, but as yet unpublished, piece of research I'm working on. 

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comment by Davidmanheim · 2020-08-18T06:24:02.871Z · LW(p) · GW(p)

I just wrote a different post which discusses this issue in slightly different terms, with a few links which might be helpful: https://www.lesswrong.com/posts/SxpNpaiTnZcyZwBGL/multitudinous-outside-views [LW · GW]