Great work! One question: You talk about forecast aggregation of probabilities for a single event like “GPT-5 will be released this year”. Have you opinions on how to extend this to aggregating entire probability distributions? E.g. for two events A and B, the probability distribution would not just include the probabilities for A and B, but also the probabilities of their Boolean combinations, like A∧B, A∨B etc. (Though three values per forecaster should be enough to calculate the rest, assuming each forecaster adheres to the probability axioms.)
Great work! One question: You talk about forecast aggregation of probabilities for a single event like “GPT-5 will be released this year”. Have you opinions on how to extend this to aggregating entire probability distributions? E.g. for two events A and B, the probability distribution would not just include the probabilities for A and B, but also the probabilities of their Boolean combinations, like A∧B, A∨B etc. (Though three values per forecaster should be enough to calculate the rest, assuming each forecaster adheres to the probability axioms.)