Longtermists sometimes argue that some causes matter extraordinarily more than others—not just thousands of times more, but 10^30 or 10^40 times more.
I don’t think any major EA or longtermist institution believes this about expected impact for 10^30 differences. There are too many spillovers for that, e.g. if doubling the world economy of $100 trillion/yr would modestly shift x-risk or the fate of wild animals, then interventions that affect economic activity have to have expected absolute value of impact much greater than 10^-30 of the most expected impactful interventions.
This argument requires that causes differ astronomically in relative cost-effectiveness. If causes A is astronomically better than cause B in absolute terms, but cause B is 50% as good in relative terms, then it makes sense for me to take a job in cause B if I can be at least twice as productive.
The premises and conclusion don’t seem to match here. A difference of 10^30x is crazy, but rejecting that doesn’t mean you don’t have huge practical differences in impact like 100x or 1000x. Those would be plenty to come close to maxing out the possible effect of differences between causes(since if you’re 1000x as good at rich-country homelessness relief as preventing pandemics, then if nothing else your fame for rich country poverty relief would be a powerful resource to help out in other areas like public endorsements of good anti-pandemic efforts).
The argument seems sort of like “some people say if you go into careers like quant trading you’ll make 10^30 dollars and can spend over a million dollars to help each animal with a nervous system. But actually you can’t make that much money even as a quant trader, so people should pay attention to fit with different careers in the world when trying to make money, since you can make more money in a field with half the compensation per unit productivity if you are twice as productive there.” The range for realistic large differences in compensation between fields (e.g. fast food cashier vs quant trading) is missing from the discussion.
You define astronomical differences at the start as ‘not just thousands of times more’ but the range to thousands of times more is where all the action is.
I don’t think any major EA or longtermist institution believes this about expected impact for 10^30 differences. There are too many spillovers for that, e.g. if doubling the world economy of $100 trillion/yr would modestly shift x-risk or the fate of wild animals, then interventions that affect economic activity have to have expected absolute value of impact much greater than 10^-30 of the most expected impactful interventions.
The premises and conclusion don’t seem to match here. A difference of 10^30x is crazy, but rejecting that doesn’t mean you don’t have huge practical differences in impact like 100x or 1000x. Those would be plenty to come close to maxing out the possible effect of differences between causes(since if you’re 1000x as good at rich-country homelessness relief as preventing pandemics, then if nothing else your fame for rich country poverty relief would be a powerful resource to help out in other areas like public endorsements of good anti-pandemic efforts).
The argument seems sort of like “some people say if you go into careers like quant trading you’ll make 10^30 dollars and can spend over a million dollars to help each animal with a nervous system. But actually you can’t make that much money even as a quant trader, so people should pay attention to fit with different careers in the world when trying to make money, since you can make more money in a field with half the compensation per unit productivity if you are twice as productive there.” The range for realistic large differences in compensation between fields (e.g. fast food cashier vs quant trading) is missing from the discussion.
You define astronomical differences at the start as ‘not just thousands of times more’ but the range to thousands of times more is where all the action is.