I feel like it’s important to say that there’s nothing wrong in principle with having extremely high or extremely low credences in things. In order for us to have credences that sum to 1 over millions of distinct possibilities, we will necessarily need to have extremely low/high credences in some propositions.
That said, yeah, I do think some of the numbers on this spreadsheet are pretty ridiculous.
Maybe one should be more hesitant to assign very low probabilities to factors in a conjunction than very high probabilities because the extreme of 100% probability should not be more controversial than omitting a factor.
With a bit of creativity someone could probably come up with dozens of verisimilar additional factor along the lines of “and false vacuum decay hasn’t happened yet.” If we then have to be humble and assign (say) no more than 99% to each of those, it just takes 10 noisy factors to bias the estimate down to ~ 90%.
In this case I went with Nate’s approach and merged the last three factors. None of them seemed silly to me, but I felt like splitting them up didn’t help my intuitions.
I guffawed when I saw Thorstads Overall ~P Doom 0.00002%, really? And some of those other probabilities weren’t much better.
Calibrate people, if you haven’t done it before do it now, here’s a handy link: https://www.openphilanthropy.org/calibration
I feel like it’s important to say that there’s nothing wrong in principle with having extremely high or extremely low credences in things. In order for us to have credences that sum to 1 over millions of distinct possibilities, we will necessarily need to have extremely low/high credences in some propositions.
That said, yeah, I do think some of the numbers on this spreadsheet are pretty ridiculous.
Maybe one should be more hesitant to assign very low probabilities to factors in a conjunction than very high probabilities because the extreme of 100% probability should not be more controversial than omitting a factor.
With a bit of creativity someone could probably come up with dozens of verisimilar additional factor along the lines of “and false vacuum decay hasn’t happened yet.” If we then have to be humble and assign (say) no more than 99% to each of those, it just takes 10 noisy factors to bias the estimate down to ~ 90%.
In this case I went with Nate’s approach and merged the last three factors. None of them seemed silly to me, but I felt like splitting them up didn’t help my intuitions.