explains how some popular approaches that might seem to differ are actually doing the same, but implicitly

Yep, I think this is a crucial point that I worry has still gotten buried a bit in my writings. This post is important background. Basically: You might say "I don't just rely on an inside view world model and EV max'ing under that model, I use outside views / heuristics / 'priors'." But it seems the justification for those other methods bottoms out in "I believe that following these methods will lead to good consequences under uncertainty in some sense" — and then I don't see how these beliefs escape cluelessness.

Poll: Is this one of your cruxes for cluelessness?

There's a cluster of responses to arguments for cluelessness I've encountered, which I'm not yet sure I understand but maybe is important. Here's my attempted summary:^[1]

Sure, maybe assigning each action a precise EV feels arbitrary. But that feeling merely reflects the psychological difficulty of generating principled numbers, for non-ideal agents like us. It's not a problem for the view that even non-ideal agents should, ultimately, evaluate actions as more or less rational based on precise EV.

If you're skeptical of cluelessness, I'd find it super helpful if you'd agree-vote if you agree with the above response or something very similar to it, and disagree-vote otherwise. ETA: added a poll widget below, please use that instead (thanks to Toby Tremlett for suggesting this). (Please don't vote if you aren't skeptical of cluelessness.) And feel free to comment with some different version of the above you'd agree with, if that difference is important for you. Thanks!

The "arbitrariness" of precise EVs is just a matter of our discomfort with picking a precise number (see above).

disagree

agree

1. ^{^}

   Some examples of sentiments that, IIUC, this summary encapsulates (emphasis mine):
   * Greaves: "I think most of us feel like we’re really just making up arbitrary numbers, but that’s really uncomfortable because precisely which arbitrary numbers we make up seems to make a difference to what we ended up doing." See also Greaves' discussion of the "decision discomfort" involved in complex cluelessness.
   * Soares: "Now, I agree that this scenario is ridiculous. And that it sucks. And I agree that picking a precise minute feels uncomfortable. And I agree that this is demanding way more precision than you are able to generate. But if you find yourself in the game, you'd best pick the minute as well as you can. When the gun is pressed against your temple, you cash out your credences."

(There’s a lot more I might want to say about this, and also don't take the precise 80% too seriously, but FWIW:)^[1]

When we do cause prioritization, we’re judging whether one cause is better than another under our (extreme) uncertainty. To do that, we need to clarify what kind of uncertainty we have, and what it means to do “better” given that uncertainty. To do that, we need to reflect on questions like:

• “Should we endorse classical Bayesian epistemology (even as an ‘ideal’)?” or
• “How do we compare actions’ ‘expected’ consequences, when we can’t conceive of all the possible consequences?”

You might defer to others who’ve reflected a lot on these questions. But to me it seems there are surprisingly few people who’ve (legibly) done so. E.g., take the theorems that supposedly tell us to be (/“approximate”?) classical Bayesians. I’ve seen very little work carefully spelling out why & how these theorems tell either ideal or bounded agents what to believe, and how to make decisions. (See also this post.)

I’ve also often seen people who are highly deferred-to in EA/rationalism make claims in these domains that, AFAICT, are straightforwardly confused or question-begging. Like “precise credences lead to ‘better decisions’ than imprecise credences” — when the whole question of what makes decisions “better” depends on our credences.

Even if someone has legibly thought a lot about this stuff, their basic philosophical attitudes might be very different from yours-upon-reflection. So I think you should only defer to them as far as you have reason to think that’s not a problem.

1. ^{^}

   Much of what I write here is inspired by discussions with Jesse Clifton.

taking the Rethink Priorities 7 - 15% numbers at face value, when the arguments for those AFAICT don't even have particular models behind them

I'm interested to hear what you think the relevant difference is between the epistemic grounding of (1) these figures vs. (2) people's P(doom)s, which are super common in LW discourse. I can imagine some differences, but the P(dooms) of alignment experts still seem very largely ass-pulled and yet also largely deferred-to.

Gotcha, so to be clear, you're saying: it would be better for the current post to have the relevant quotes from the references, but it would be even better to have summaries of the explanations?

(I tend to think this is a topic where summaries are especially likely to lose some important nuance, but not confident.)

That's helpful to know, thanks! I currently don't have time for this, but (edit) might add quotes later.

Most of the added value comes from the synthesis

Could you please clarify what you mean by this?

Maybe you need some account of transworld identity (or counterparts) to match these lives across possible worlds

That's the concern, yeah. When I said ”some nontrivially likely possible world containing an astronomical number of happy lives”, I should have said these were happy experience-moments, which (1) by definition only exist in the given possible world, and (2) seem to be the things I ultimately morally care about, not transworld persons.^[1] Likewise each of the experience-moments of the lives directly saved by the AMF donation only exist in a given possible world.

1. ^{^}

   (Or spacetime regions.)

Thanks for this post, Magnus! While I’m still uncompelled by your arguments in “Why give weight to a scope-adjusted view” for the reasons discussed here and here, I’ll set that aside and respond to the “Asymmetry in practical recommendations”.

Suppose that (i) the normative perspective from which we’re clueless (e.g., impartial consequentialism plus my framework here) says both A and B are permissible, and (ii) all other normative perspectives we give weight to say only A is permissible. In that case, I’d agree we should do A, no matter how minuscule the weight we give to the perspectives in (ii).

But realistically, our situation doesn’t seem that clean. Take {A = “donate to the Humane Slaughter Association”, B = “spend that money on yourself”}. It seems that different scope-adjusted views might give the opposite verdict here. Let T be the time horizon beyond which the HSA donation might lead to, say, increased wild animal suffering via increasing the price of meat for larger farmed animals.

• If we discount fast enough, the effects before T (preventing painful slaughter) dominate ⇒ A is better than B.
• If we discount more slowly (but not so slowly that we’re clueless!), the backfire effect on wild animals after T might dominate ⇒ B is better than A.

(In practice things might be much more complicated than this model lets on. It’s just an illustration.)

We might try to put meta-normative weights on these different discount rates. But I expect the relative weights to be arbitrary, which would make us clueless all over again from a consequentialist perspective. (I’m not saying our normative views need to be precisely specified — they can and will be vague — but we need some perhaps-vague overall reason to think the A-favoring perspectives outweigh the B-favoring perspectives. And I’m still keen for people to think about what that kind of reason might be!)

Unfortunately not that "succinct" :) but I argue here that cluelessness-ish arguments defeat the impartial altruistic case for any intervention, longtermist or not. Tl;dr: our estimates of the sign of our net long-term impact are arbitrary. (Building on Mogensen (2021).)

(It seems maybe defensible to argue something like: "We can at least non-arbitrarily estimate net near-term effects. Whereas we're clueless about the sign of any particular (non-'gerrymandered') long-term effect (or, there's something qualitatively worse about the reasons for our beliefs about such effects). So we have more reason to do interventions with the best near-term effects." This post gives the strongest case for that I'm aware of. I'm not personally convinced, but think it's worth investigating further.)

The "lower meat production" ⇒ "higher net primary productivity" ⇒ "higher wild animal suffering" connection seems robust to me. Or not that much less robust than the intended benefit, at least.