The simple response to the unilateralist curse under the standard setting is to aggregate opinions amongst the people in the reference class, and then do the majority vote.
A particular flawed response is to look for N opinions that say “intervening is net negative” and intervene iff you cannot find that many opinions. This sacrifices value and induces a new unilateralist curse on people who think the intervention is negative. (Example.)
However, the hardest thing about the unilateralist curse is figuring out how to define the reference class in the first place.
I didn’t get it… is the problem with the “look for N opinions” response that you aren’t computing the denominator (|”intervening is positive”| + |”intervening is negative”|)?
Yes, that’s the problem. In this situation, if N << population / 2, you are likely to not intervene even when the intervention is net positive; if N >> population / 2, you are likely to intervene even when the intervention is net negative.
(This is under the simple model of a one-shot decision where each participant gets a noisy observation of the true value with the noise being iid Gaussians with mean zero.)
The simple response to the unilateralist curse under the standard setting is to aggregate opinions amongst the people in the reference class, and then do the majority vote.
A particular flawed response is to look for N opinions that say “intervening is net negative” and intervene iff you cannot find that many opinions. This sacrifices value and induces a new unilateralist curse on people who think the intervention is negative. (Example.)
However, the hardest thing about the unilateralist curse is figuring out how to define the reference class in the first place.
I didn’t get it… is the problem with the “look for N opinions” response that you aren’t computing the denominator (|”intervening is positive”| + |”intervening is negative”|)?
Yes, that’s the problem. In this situation, if N << population / 2, you are likely to not intervene even when the intervention is net positive; if N >> population / 2, you are likely to intervene even when the intervention is net negative.
(This is under the simple model of a one-shot decision where each participant gets a noisy observation of the true value with the noise being iid Gaussians with mean zero.)