To fill out the details of what you’re getting at, I think you’re saying “the welfare level of an animal is X% of its capacity C. We’re confident of both X and C in the given scenario for animal A is high enough that it’s better to help animal A than animal B”. That may be correct, but you’re accepting that than you can know the welfare levels because you know the percentage of the capacity. But then I can make the same claim again: why should we be confident we’ve got the percentage of the capacity right?
I agree we should, in general, use inference to the best explanation. I’m not sure we know how to do that when we don’t have access to the relevant evidence (the private, subjective states) to draw inferences. If it help, trying putting on the serious sceptic’s hat and ask “okay, we might feel confident animal A is suffering more than animal B, and we do make these sort of judgement the whole time, but what justifies this confidence?”. What I’d really like to understand (not necessary from you—I’ve been thinking about this for a while!) is what the chain of reasoning is that would go into that justification.
But then I can make the same claim again: why should we be confident we’ve got the percentage of the capacity right?
I think even if we’re not confident, bounds on welfare capacity can still be useful. For example, if I know that A produces X net units of good (in expectation), and B produces between Y and Z net units of good, then under risk-neutral expected value maximization, X < Y would tell me that B’s better, and X > Z would tell me that A’s better. The problem is where Y < X < Z. And we can build a distribution over the percentage of capacity or do a sensitivity analysis, something similar to this, say.
Thanks for the thoughtful reply!
To fill out the details of what you’re getting at, I think you’re saying “the welfare level of an animal is X% of its capacity C. We’re confident of both X and C in the given scenario for animal A is high enough that it’s better to help animal A than animal B”. That may be correct, but you’re accepting that than you can know the welfare levels because you know the percentage of the capacity. But then I can make the same claim again: why should we be confident we’ve got the percentage of the capacity right?
I agree we should, in general, use inference to the best explanation. I’m not sure we know how to do that when we don’t have access to the relevant evidence (the private, subjective states) to draw inferences. If it help, trying putting on the serious sceptic’s hat and ask “okay, we might feel confident animal A is suffering more than animal B, and we do make these sort of judgement the whole time, but what justifies this confidence?”. What I’d really like to understand (not necessary from you—I’ve been thinking about this for a while!) is what the chain of reasoning is that would go into that justification.
I think even if we’re not confident, bounds on welfare capacity can still be useful. For example, if I know that A produces X net units of good (in expectation), and B produces between Y and Z net units of good, then under risk-neutral expected value maximization, X < Y would tell me that B’s better, and X > Z would tell me that A’s better. The problem is where Y < X < Z. And we can build a distribution over the percentage of capacity or do a sensitivity analysis, something similar to this, say.