One thing that occurs to me is that each analysis, such as the Putin one, can be thought of as a function hypothesis.
It takes as inputs the variables:
Russian demographics
healthy lifestyle
family history
facial swelling
hair present
And is outputting the probability 86%, where the function is
P = F(demographics, lifestyle, history, swelling, hair) and then each term is being looked up in some source, which has a data quality, and the actual equation seems to be a mix of Bayes and simple probability calculations.
There are other variables not considered, and other valid reasoning tracks. You could take into account the presence of oncologists in putin’s personal staff. Intercepted communication possibly discussing it. Etc. I’m not here to discuss the true odds of putin developing cancer, but note that if the above is “function A”, and another function that takes into account different information is “function B”, you should be aggregating all valid functions, forming a “probability forest”.
Perhaps you weight each one by the likelihood of the underlying evidence being true. For example each of the above facts is effectively 100% true except for the hair present (putin could have received a hair transplant) and family history (some relative causes of death could be unknown or suspicious that it was cancer)
This implies a function “A’n”, where we assume and weight in the probability that each combination of the underlying variables has the opposite value. For example, if pHair_Present = 0.9, A’ has one permutation where the hair is not present due to a transplant.
This hints at why a panel of superforecasters is presently the best we can do. Many of them do simple reasoning like this and we see it in the comment section on Manifold. But each individual human doesn’t have the time to think of 100 valid hypotheses and to calculate the resulting probability, many manifold bettors seem to usually consider 1 and bet their mana.
An AI system (LLM based with plugin access) able to do the legwork here would be very useful...
One thing that occurs to me is that each analysis, such as the Putin one, can be thought of as a function hypothesis.
It takes as inputs the variables:
Russian demographics
healthy lifestyle
family history
facial swelling
hair present
And is outputting the probability 86%, where the function is
P = F(demographics, lifestyle, history, swelling, hair) and then each term is being looked up in some source, which has a data quality, and the actual equation seems to be a mix of Bayes and simple probability calculations.
There are other variables not considered, and other valid reasoning tracks. You could take into account the presence of oncologists in putin’s personal staff. Intercepted communication possibly discussing it. Etc. I’m not here to discuss the true odds of putin developing cancer, but note that if the above is “function A”, and another function that takes into account different information is “function B”, you should be aggregating all valid functions, forming a “probability forest”.
Perhaps you weight each one by the likelihood of the underlying evidence being true. For example each of the above facts is effectively 100% true except for the hair present (putin could have received a hair transplant) and family history (some relative causes of death could be unknown or suspicious that it was cancer)
This implies a function “A’n”, where we assume and weight in the probability that each combination of the underlying variables has the opposite value. For example, if pHair_Present = 0.9, A’ has one permutation where the hair is not present due to a transplant.
This hints at why a panel of superforecasters is presently the best we can do. Many of them do simple reasoning like this and we see it in the comment section on Manifold. But each individual human doesn’t have the time to think of 100 valid hypotheses and to calculate the resulting probability, many manifold bettors seem to usually consider 1 and bet their mana.
An AI system (LLM based with plugin access) able to do the legwork here would be very useful...