Thanks for sharing this. My (quick) reading is that the idea is to treat expected value calculations not as gospel, but as if they are experiments with estimated error intervals. These experiments should then inform, but not totally supplant, our prior. That seems sensible for givewell’s use cases, but I don’t follow the application to pascal’s mugging cases or better supported fanatical projects. The issue is that they don’t have expected value calculations that make sense to regard as experiments.
Perhaps the proposal is that we should have a gut estimate and a gut confidence based on not thinking through the issues much, and another estimate based on making some guesses and plugging in the numbers, and we should reconcile those. I think this would be wrong. If anything, we should take our Bayesian prior to be our estimate after thinking through all the issues, (but perhaps before plugging in all of the exact numbers). If you’ve thought through all the issues above, I think it is appropriate to allow an extremely high expected value for fanatical projects even before trying to make a precise calculation. Or at least it is reasonable for your prior to be radically uncertain.
What do you think of the Bayesian solution, where you shrink your EV estimate towards a prior (thereby avoiding the fanatical outcomes)?
Thanks for sharing this. My (quick) reading is that the idea is to treat expected value calculations not as gospel, but as if they are experiments with estimated error intervals. These experiments should then inform, but not totally supplant, our prior. That seems sensible for givewell’s use cases, but I don’t follow the application to pascal’s mugging cases or better supported fanatical projects. The issue is that they don’t have expected value calculations that make sense to regard as experiments.
Perhaps the proposal is that we should have a gut estimate and a gut confidence based on not thinking through the issues much, and another estimate based on making some guesses and plugging in the numbers, and we should reconcile those. I think this would be wrong. If anything, we should take our Bayesian prior to be our estimate after thinking through all the issues, (but perhaps before plugging in all of the exact numbers). If you’ve thought through all the issues above, I think it is appropriate to allow an extremely high expected value for fanatical projects even before trying to make a precise calculation. Or at least it is reasonable for your prior to be radically uncertain.
There are ways to deal with Pascal’s Mugger with leverage penalties, which IIRC deal with some problems but are not totally satisfying in extremes.