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Econ PhD student at Oxford and research associate at the Global Priorities Institute. I'm slightly less ignorant about economic theory than about everything else.



To my mind, the first point applies to whatever resources are used throughout the future, whether it’s just the earth or some larger part of the universe.

I agree that the number/importance of welfare subjects in the future is a crucial consideration for how much to do longtermist as opposed to other work. But when comparing longtermist interventions—say, splitting a budget between lowering the risk of the world ending and proportionally increasing the fraction of resources devoted to creating happy artificial minds—it would seem to me that the “size of the future” typically multiplies the value of both interventions equally, and so doesn’t matter.

Ok--at Toby's encouragement, here are my thoughts:

This is a very old point, but to my mind, at least from a utilitarian perspective, the main reason it's worth working on promoting AI welfare is the risk of foregone upside. I.e. without actively studying what constitutes AI welfare and advocating for producing it, we seem likely to have a future that's very comfortable for ourselves and our descendants--fully automated luxury space communism, if you like--but which contains a very small proportion of the value that could have been created by creating lots of happy artificial minds. So concern for creating AI welfare seems likely to be the most important way in which utilitarian and human-common-sense moral recommendations differ.

It seems to me that the amount of value we could create if we really optimized for total AI welfare is probably greater than the amount of disvalue we'll create if we just use AI tools and allow for suffering machines by accident, since in the latter case the suffering would be a byproduct, not something anyone optimizes for.

But AI welfare work (especially if this includes moral advocacy) just for the sake of avoiding this downside also seems valuable enough to be worth a lot of effort on its own, even if suffering AI tools are a long way off. The animal analogy seems relevant: it's hard to replace factory farming once people have started eating a lot of meat, but in India, where Hinduism has discouraged meat consumption for a long time, less meat is consumed and so factory farming is evidently less widespread.

So in combination, I expect AI welfare work of some kind or another is probably very important. I have almost no idea what the best interventions would be or how cost-effective they would be, so I have no opinion on exactly how much work should go into them. I expect no one really knows at this point. But at face value the topic seems important enough to warrant at least doing exploratory work until we have a better sense of what can be done and how cost-effective it could be, only stopping in the (I think unlikely) event that we can say with some confidence that the best AI welfare work to be done is worse than the best work that can be done in other areas.

The point that it's better to save people with better lives than people with worse lives, all else equal, does make sense (at least from a utilitarian perspective). So you're right that [$ / lives saved] is not a perfect approach. I do think it's worth acknowledging this...!

But the right correction isn't to use VSLs. The way I'd put it is: a person's VSL--assuming it's been ideally calculated for each individual, putting aside issues about how governments estimate it in practice--is how many dollars they value as much as slightly lowering their chance of death. So the fact that VSLs differ across people mixes together two things: a rich person might have a higher VSL than a poor person (1) because the rich person values their life more, or (2) because the rich person values a dollar less. The first thing is right to correct for (from a utilitarian perspective), but as other commenters have noted, the second isn't.

My guess is that the second factor baked into the VSL is bigger in most real-world comparisons we might want to make, so that it's less of a mistake to just try to maximize [$ / lives saved] than to try to maximize [$ / (lives saved * VSL)].

I don't follow--are you saying that (i) AI safety efforts so far have obviously not actually accomplished much risk-reduction, (ii) that this is largely for risk compensation reasons, and (iii) that this is worth emphasizing in order to prevent us from carrying on the same mistakes?

If so, I agree that if (i)-(ii) are true then (iii) seems right, but I'm not sure about (i) and (ii). But if you're just saying that it would be good to know whether (i)-(ii) are true because if they are then it would be good to do (iii), I agree.

Whoops, thanks! Issues importing from the Google doc… fixing now.

Good to hear, thanks!

I‘ve just edited the intro to say: it’s not obvious to me one way or the other whether it's a big deal in the AI risk case. I don't think I know much about the AI risk case (or any other case) to have much of an opinion, and I certainly don't think anything here is specific enough to come to a conclusion in any case. My hope is just that something here makes it easier to for people who do know about particular cases to get started thinking through the problem.

If I have to make a guess about the AI risk case, I'd emphasize my conjecture near the end, just before the "takeaways" section, namely that (as you suggest) there currently isn't a ton of restraint, so (b) mostly fails, but that this has a good chance of changing in the future:

Today, while even the most advanced AI systems are neither very capable nor very dangerous, safety concerns are not constraining  much below . If technological advances unlock the ability to develop systems which offer utopia if their deployment is successful, but which pose large risks, then the developer’s choice of  at any given  is more likely to be far below , and the risk compensation induced by increasing  is therefore more likely to be strong.

If lots/most of AI safety work (beyond evals) is currently acting more "like evals" than like pure "increases to S", great to hear--concern about risk compensation can just be an argument for making sure it stays that way!

Thanks for noting this. If in some case there is a positive level of capabilities for which P is 1, then we can just say that the level of capabilities denoted by C = 0 is the maximum level at which P is still 1. What will sort of change is that the constraint will be not C ≥ 0 but C ≥ (something negative), but that doesn't really matter since here you'll never want to set C<0 anyway. I've added a note to clarify this.

Maybe a thought here is that, since there is some stretch of capabilities along which P=1, we should think that P(.) is horizontal around C=0 (the point at which P can start falling from 1) for any given S, and that this might produce very different results from the  example in which there would be a kink at C=0. But no--the key point is whether increases to S change the curve in a way that widens as C moves to the right, and so "act as price decreases to C", not the slope of the curve around C=0. E.g. if  (for , and 0 above), then in the k=0 case where the lab is trying to maximize , they set , and so P is again fixed (here, at 2/3) regardless of S.

Hey David, I've just finished a rewrite of the paper which I'm hoping to submit soon, which I hope does a decent job of both simplifying it and making clearer what the applications and limitations are: https://philiptrammell.com/static/Existential_Risk_and_Growth.pdf

Presumably the referees will constitute experts on the growth front at least (if it's not desk rejected everywhere!), though the new version is general enough that it doesn't really rely on any particular claims about growth theory.

Hold on, just to try wrapping up the first point--if by "flat" you meant "more concave", why do you say "I don't see how [uncertainty] could flatten out the utility function. This should be in "Justifying a more cautious portfolio"?"

Did you mean in the original comment to say that you don't see how uncertainty could make the utility function more concave, and that it should therefore also be filed under "Justifying a riskier portfolio"?

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