Note: I donāt work for 80,000 Hours, and I donāt know how closely the people who wrote that article/āproduced their āscaleā table would agree with me.
For that particular number, I donāt think there was an especially rigorous reasoning process. As they say when explaining the table in their scale metric, āthe tradeoffs across the columns are extremely uncertainā.
That is, I donāt think that thereās an obvious chain of logic from āfactory farming endsā to āthe future is 0.01% betterā. Figuring out what constitutes āthe value of the futureā is too big a problem to solve right now.
However, there are some columns in the table that do seem easier to compare to animal welfare. For example, you can see that a scale of ā10ā (what factory farming gets) means that roughly 10 million QALYs are saved each year.
So a scale of ā10ā means (roughly) that something happens each year which is as good as 10 million people living for another year in perfect health, instead of dying.
Does it seem reasonable that the annual impact of factory farming is as bad as 10 million people losing a healthy year of their lives?
If you think that does sound reasonable, then a scale score of ā10ā for ending factory farming should be fine. But you might also think that one of those two thingsāthe QALYs, or factory farmingāis much more important than the other. That might lead you to assign a different scale score to one of them when you try to prioritize between causes.
Of course, these comparisons are far from perfectly empirical. But at some point, you have to say āokay, outcome A seems about as good/ābad as outcome Bā in order to set priorities.
Note: I donāt work for 80,000 Hours, and I donāt know how closely the people who wrote that article/āproduced their āscaleā table would agree with me.
For that particular number, I donāt think there was an especially rigorous reasoning process. As they say when explaining the table in their scale metric, āthe tradeoffs across the columns are extremely uncertainā.
That is, I donāt think that thereās an obvious chain of logic from āfactory farming endsā to āthe future is 0.01% betterā. Figuring out what constitutes āthe value of the futureā is too big a problem to solve right now.
However, there are some columns in the table that do seem easier to compare to animal welfare. For example, you can see that a scale of ā10ā (what factory farming gets) means that roughly 10 million QALYs are saved each year.
So a scale of ā10ā means (roughly) that something happens each year which is as good as 10 million people living for another year in perfect health, instead of dying.
Does it seem reasonable that the annual impact of factory farming is as bad as 10 million people losing a healthy year of their lives?
If you think that does sound reasonable, then a scale score of ā10ā for ending factory farming should be fine. But you might also think that one of those two thingsāthe QALYs, or factory farmingāis much more important than the other. That might lead you to assign a different scale score to one of them when you try to prioritize between causes.
Of course, these comparisons are far from perfectly empirical. But at some point, you have to say āokay, outcome A seems about as good/ābad as outcome Bā in order to set priorities.