the personal probability estimates are pulled out of my ‘air’ of intuitive judgments. You are allowed to play with the numbers according to your intuitive judgments. Breaking down the total estimate into factors allows you to make more accurate estimates, because you better reflect on all your beliefs that are relevant for the estimate
How do you determine whether something is 0.90, 0.95, 0.99, or some other number?
In your summary, you state that animal causes have a combined 7⁄12 chance of being the top priority, whereas human causes have a combined 5⁄12 chance. However, the error margins are huge, with the original wild animals priority having “wide-margins” of 25-90%.
It does not seem to me that there can be any conclusive determinations made with this when the options are so close relatively and the margins so wide. The calculation is entirely subjective based on your own admission. I am afraid that giving it a veneer of objectivity in this way is in fact misleading, not clarifying.
As mentioned, those percentages wher my own subjective estimates, and they were determined based on the considerations that I mentioned (“This estimate is based on”). When I clearly state that these are my personal, subjective estimates, I don’t think it is misleading: it does not give a veneer of objectivity.
The clarifying part is that you can now decide whether you agree or disagree with the probability estimates. Breaking the estimate into factors helps you to clarify the relevant considerations and improves your accuracy. It is better than simply guessing the overall estimate of the probability that wild animal suffering is the priority.
If you don’t like the wide margins, perhaps you can improve the estimates? But knowing we often have an overconfidence bias (our error estimates are often too narrow), we should a priori not expect narrow error margins and we should correct this bias by taking wider margins.
the personal probability estimates are pulled out of my ‘air’ of intuitive judgments. You are allowed to play with the numbers according to your intuitive judgments. Breaking down the total estimate into factors allows you to make more accurate estimates, because you better reflect on all your beliefs that are relevant for the estimate
What is the actual calculations you used?
For the wild animal welfare lower bound: 0.99 * 0.99 * 0⁄75 * 0.99 * 0.95 * 0.9 * 0.8 * 0.9 * 0.8 * 0.9 * 0.9 * 0.8 * 0.95 * 0.95 = 21% ?
How do you determine whether something is 0.90, 0.95, 0.99, or some other number?
In your summary, you state that animal causes have a combined 7⁄12 chance of being the top priority, whereas human causes have a combined 5⁄12 chance. However, the error margins are huge, with the original wild animals priority having “wide-margins” of 25-90%.
It does not seem to me that there can be any conclusive determinations made with this when the options are so close relatively and the margins so wide. The calculation is entirely subjective based on your own admission. I am afraid that giving it a veneer of objectivity in this way is in fact misleading, not clarifying.
As mentioned, those percentages wher my own subjective estimates, and they were determined based on the considerations that I mentioned (“This estimate is based on”). When I clearly state that these are my personal, subjective estimates, I don’t think it is misleading: it does not give a veneer of objectivity.
The clarifying part is that you can now decide whether you agree or disagree with the probability estimates. Breaking the estimate into factors helps you to clarify the relevant considerations and improves your accuracy. It is better than simply guessing the overall estimate of the probability that wild animal suffering is the priority.
If you don’t like the wide margins, perhaps you can improve the estimates? But knowing we often have an overconfidence bias (our error estimates are often too narrow), we should a priori not expect narrow error margins and we should correct this bias by taking wider margins.