I agree that there are people who don’t need this warning most of the time. Because they already double and triple check their estimates and are the first ones to admit to their fallibility. “Most of us” are habitually overconfident though. I also agree that the circumstances matter a lot, and some people in some circumstances can be accurate at 1% level, but most people in most circumstances aren’t. I’m guessing that superforecasters would not even try to estimate anything at 1% level, realizing they cannot do it well enough. We are most fallible when we don’t even realize we are calculating odds (there is a suitable HPMOR quote about that, too). Your example of giving a confidence interval or a range of probabilities is definitely an improvement over the usual Bayesian point estimates, but I don’t see any easily accessible version of the Bayes formula for ranges, though admittedly I’m not looking hard enough. In general, thinking in terms of distributions, not point estimates, seems like it would be progress. Mathematicians and physicists do that already in a professional setting.
I agree that there are people who don’t need this warning most of the time. Because they already double and triple check their estimates and are the first ones to admit to their fallibility. “Most of us” are habitually overconfident though. I also agree that the circumstances matter a lot, and some people in some circumstances can be accurate at 1% level, but most people in most circumstances aren’t. I’m guessing that superforecasters would not even try to estimate anything at 1% level, realizing they cannot do it well enough. We are most fallible when we don’t even realize we are calculating odds (there is a suitable HPMOR quote about that, too). Your example of giving a confidence interval or a range of probabilities is definitely an improvement over the usual Bayesian point estimates, but I don’t see any easily accessible version of the Bayes formula for ranges, though admittedly I’m not looking hard enough. In general, thinking in terms of distributions, not point estimates, seems like it would be progress. Mathematicians and physicists do that already in a professional setting.