Basically, there is nothing do disagree here: DA is working, but gives weaker predictions, than actual information about distributions. That is why we should try to use DA in domains where we don’t have initial distribution, just to get order of magnitude estimation.
The more interesting question is how to combine situations where we have some incomplete information about actual distribution and the age of one random object. It seems that Caves suggest to ignore DA in this case.
(But there is also Carter’s approach to DA, where DA inference is used to update information about known future x-risks, based on fact that we are before it.)
In some cases DA may be stronger than incomplete information provided by other sources. For example, if one extraterrestrial knows for sure, that any mammal life expectancy is less than 1 million years, and than he finds one human being with age 60 years, DA gives him that medium human life expectancy is less than 1000 years. In this case DA is much stronger than prior.
Basically, there is nothing do disagree here: DA is working, but gives weaker predictions, than actual information about distributions. That is why we should try to use DA in domains where we don’t have initial distribution, just to get order of magnitude estimation.
The more interesting question is how to combine situations where we have some incomplete information about actual distribution and the age of one random object. It seems that Caves suggest to ignore DA in this case. (But there is also Carter’s approach to DA, where DA inference is used to update information about known future x-risks, based on fact that we are before it.)
In some cases DA may be stronger than incomplete information provided by other sources. For example, if one extraterrestrial knows for sure, that any mammal life expectancy is less than 1 million years, and than he finds one human being with age 60 years, DA gives him that medium human life expectancy is less than 1000 years. In this case DA is much stronger than prior.