.@bryan_caplan and he has the bets to prove it!
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I used to think this, but have come to believe that Bryan's betting is overrated. His only strategy is to wait for people to make predictions far outside the norm and then shame-bet them. He basically never takes a financial stand on less certain outcomes.
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Yeah, I don't think the domain in which he wins bets generalizes that strongly
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(I figure Bryan probably agrees with this, but I'd be curious to hear why not, if I'm wrong)
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Since I'm open to bets on anything with anyone, I think it does generalize pretty strongly.https://www.econlib.org/archives/2017/06/what_a_bet_show.html …
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I was very unclear, above - this is what I meant by the "domain" you win bets in, does this seem wrong?https://twitter.com/juliagalef/status/1095341886879948805 …
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Roughly correct, then.https://www.econlib.org/archives/2016/05/why_i_win.html …
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Reading my phrasing again ("Yeah, I don't think the domain in which he wins bets generalizes that strongly") I'd revise it somewhat. The domain of "identifying overconfident deviations from base rates" is actually quite significant, which I don't think my wording made clear.
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This question is a bit like 'who do you agree with?'
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Well, hopefully meeting the "rarely wrong" standard doesn't just mean "says things I agree with"! I'd count things like - makes predictions that come true - expresses skepticism about things that later turn out to be false - makes arguments that aren't credibly rebutted
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I acknowledge somebody could answer your question and be correct. But people will certainly disagree about whether their fav intellectual's arguments have been rebutted & I suspect there will be more room for argument in the others than you might think. so in practice...
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Oh definitely, the answers will still be significantly subjective
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It'll be interesting to read them
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I'd say
@RobertJShiller. But that's just a guess, as are almost all the others offered, because calibration of judgment is almost never properly tested, no matter how important that judgment is. (Honourable exception:@bryan_caplan)@PTetlock -
Yes, indeed. I figured people would use rough heuristics like - Have they made predictions/bets (w/high qualitative confidence) that came true - Have they expressed skepticism about things that turned out to be false/exaggerated - Have people noted major flaws in their arguments
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well, different experts are well-calibrated to different degrees in different contexts... if you put a gun to my head I'd probably go with my ex-boss
@dineshraju as someone I would trust to be careful with his claims -
and... should well-calibrated really mean "rarely wrong when expressing high confidence"?
this can be gamed by minimizing utterances. I'm reminded of this Bezos quote – "in business, when you step up to the plate, you can score 1,000 runs" – this is good calibration IMOpic.twitter.com/4PGO3zeXbG
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This is an aspect of "accuracy" that isn't captured by "well-calibrated", yeah But presumably someone who rarely makes any bets or claims at all won't be an expert / public figure
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IMHO well-calibrated people seek out domains where their claims, when correct, can have outsized impact. Being right in such domains inevitably depends on many uncontrollable factors. So I'd look for successful folks in domains where you're usually wrong even when well-calibrated
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Also I think outsized business success involves some path dependence. So instead of founders, I'd look for successful investors who've had many swings at bat & are dedicated to searching for the truth to make better investment decisions. Charlie Munger and
@RayDalio come to mind - 1 more reply
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