www.jimbuhler.site
Also on LessWrong and Substack, with different essays.
just getting wide distributions for the cost-effectiveness
A normal Gaussian distribution? If so, then you still think the value in the middle of the curve is uniquely appropriate (even if barely so). To me, that's the key difference between A) imprecision and B) precision with severe credal fragility. The former assumes you can't non-arbitrarily pin down a precise credence at all, while the latter assumes you still can.
If VOI is overwhelmingly high, both A and B might recommend research, such that the difference doesn't matter. But it matters a lot at least in situations where actors want to fund non-research things (because they think VOI is not that high or whatever). Then, A and B deeply disagree on what should be done.
Helpful thanks! Related thoughts from Clifton, here. But you actually do not object to UNSHARP (to some degree) for limited agents like us, then, right?
Do you agree with the other's (EDIT: authors') non-endorsement of Uniqueness? My impression was that you'd endorse SHARP because you think your sharp credence is uniquely appropriate. If not, why endorse this one rather than another sharp one that isn't any less appropriate?
Say I compare different GHD interventions that help the worst off. I know that most such interventions are not crazy effective and that it's easy to under or overestimate those with little evidence. I have a good reference class. If someone tells me about a new intervention in the area, I don't expect it to be crazy good. It's much more likely to be close to the mean. I have a prior expectation. If my math tells me there's some poorly-studied intervention that beats the one that has consistently proven most effective so far, this weak evidence should not override my prior expectation. The math without accounting for my prior would give an overestimated number, surely.
But now say someone presents me with an x-risk intervention. I don't have a "cross-cause prior" that says that an intervention from any cause is close to the GHD mean, do I?[1] If I understand your post correctly, you are implicitly assuming we do have such a cross-cause prior. (Otherwise, there wouldn't be any OC-related reason to downweight the x-risk intervention.)[2] Is that correct?
Hi Vasco. Agreed, I think the relationship between p(sentience) and welfare ranges is very indeterminate.
Also, to be clear, I think p(sentience) is very relevant in theory. It's just that, in practice, it seems like we have evidence that warrants ruling out assigning tiny probabilities of sentience to, e.g., shrimp and ants. However, I don't think we have that for very narrow welfare ranges, and this is where uncertainty and disagreements lie.
The empirical evidence that shrimp have small brains detracts from this probability, but not by much.
I very much agree that pretty much whatever our prior should be, the available evidence does not justify substantially updating away from it. I'm just uncertain about what the prior should be (see below).
I think that conditioning on p(sentience) is sufficient to justify a non-negligible probability of similar levels of welfare range in the absence of any further empirical evidence.
Yeah, agreed that's the crux! :) I think you are applying a principle of indifference (POI) across welfare subjects (or have a significant credence in such a move, at least).[1] While I actually also have sympathy for something of the sort,[2] it is widely criticized in the literature on cluelessness and decision-making under uncertainty. Here's a list of challenges and possible responses taken from a rough paper draft of mine on this exact topic:
A tl;dr from Claude that I like: ignorance about X's welfare range doesn't automatically justify treating X's welfare as if it equals human welfare — it might just justify suspending judgment. The move from "we don't know the ratio" to "assume the ratio is 1" needs much more justification.
See also Dickens and Shepherd et al. (2023), who endorse this move.
Especially as an alternative to defaulting to our intuitions or "invertebrates don't matter at all until proven otherwise".
One could nitpick that there's technically no complex cluelessness if we're truly uninformed and ignore the (conflicting) evidence. But in that case, sure, maybe we can start with POI, but then we update towards agnosticism once we consider evidence, so the POI argument for giving everyone the same moral weight wouldn't work.
I just had a naive illumination. Say that sentience first appeared in two different simple creatures, independently, at the same time:
Judging by what you've written in the post and comments, you could give two different arguments for why Dolores would have lower fitness than Mildred:
What am I misunderstanding/missing?
it seems to me to be very unreasonable to be confident that simpler brains most likely have much smaller welfare ranges
I agree, and I absolutely did not mean to defend this. What I defend is that, in the absence of a good argument based on welfare ranges and not p(sentience), we don't know if the welfare range of simpler animals is below or above the bar above which their welfare would dominate over that of more complex animals (not that it is below!).
But you disagree with my a priori agnosticism because you think we should (roughly) stick to some precise-ish prior welfare ranges in the absence of significant evidence pointing one way or the other, correct? (And this prior would give simpler animals enough weight for them to likely dominate.) This would explain your disagreement with what you quote.[1] I was implicitly assuming that our prior should be an agnostic imprecise one that offers no action-guidance on its own.
If that's not where the disagreement is, I don't see how "a presumption of a reasonable probability of a welfare range that is not too small and no significant evidence against it" does not count as "evidence of a welfare range that is not too insignificant." Maybe you're just worried my imprecise phrasing will, while technically correct, lead readers to set the bar too high?
Curious what motivated you to spend time assessing the impact of bird-safe glass on arthropods, specifically, then. Were you hoping to find out that bird effects dominated but found and shared the opposite unsatisfying results? Or maybe you think "here's another example showing how indirect effects on tiny animals may dominate" and that this will convince some people to also prioritize (i) and (ii)? (people who were not convinced by your previous largely-overlapping posts but might by this one?)
One thing is whoever does not reject UNSHARP might not have severely imprecise credences about everything. I might believe that
Then, I'd probably prioritize intervention 2. If I instead endorsed SHARP, I might favor intervention 1 (because of a sufficient 51% credence 1 is good). (I'm actually not sure about this, though. One could argue that 1 and 2 remain incomparable and that I have no reason to favor 2 over 1.)
Another thing, assuming there is no 2-like intervention, is that the criterion to pick could be something other than "act straightforwardly as if you were endorsing SHARP". It could instead be, e.g., some (other) form of bracketing.