The example used here is a stochastic process, which is a case where resilience of a subjective probability can be easily described with a probability distribution and Bayesian updates on observations. But the most important applications of the idea are one-off events with mainly epistemic uncertainty. Is there a good example we could include for that? Maybe a description of how you might express/quantify the resilience of a forecast for a past event whose outcome is not known yet?
I don't have time to do that myself right now, plus I think other people in the EA community are more knowledgeable about this stuff than me, so hopefully someone else can do that!
Otherwise it's possible I'll circle back in a few weeks/months.
The example used here is a stochastic process, which is a case where resilience of a subjective probability can be easily described with a probability distribution and Bayesian updates on observations. But the most important applications of the idea are one-off events with mainly epistemic uncertainty. Is there a good example we could include for that? Maybe a description of how you might express/quantify the resilience of a forecast for a past event whose outcome is not known yet?
I think this entry could be improved and expanded using some of the content, terms/concepts, and/or links from this shortform of mine: https://www.lesswrong.com/posts/gcEayv6HtBogfov2n/michaela-s-shortform?commentId=otZLATzjTfMRuE9JA
I don't have time to do that myself right now, plus I think other people in the EA community are more knowledgeable about this stuff than me, so hopefully someone else can do that!
Otherwise it's possible I'll circle back in a few weeks/months.