Lukas Finnveden

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Research analyst at Open Philanthropy. All opinions are my own.


Project ideas for making transformative AI go well, other than by working on alignment


Topic contributions

Here's one line of argument:

  • Positive argument in favor of humans: It seems pretty likely that whatever I'd value on-reflection will be represented in a human future, since I'm a human. (And accordingly, I'm similar to many other humans along many dimensions.)
    • If AI values where sampled ~randomly (whatever that means), I think that the above argument would be basically enough to carry the day in favor of humans.
  • But here's a salient positive argument in favor of why AIs' values will be similar to mine: People will be training AIs to be nice and helpful, which will surely push them towards better values.
    • However, I also expect people to be training AIs for obedience and, in particular, training them to not disempower humanity. So if we condition on a future where AIs disempower humanity, we evidentally didn't have that much control over their values. This signiciantly weakens the strength of the argument "they'll be nice because we'll train them to be nice".
      • In addition: human disempowerment is more likely to succeed if AIs are willing to egregiously violate norms, such a by lying, stealing, and killing. So conditioning on human disempowerment also updates me somewhat towards egregiously norm-violating AI. That makes me feel less good about their values.
    • Another argument is that, in the near term, we'll train AIs to act nicely on short-horizon tasks, but we won't particularly train them to deliberate and reflect on their values well. So even if "AIs' best-guess stated values" are similar to "my best-guess stated values", there's less reason to belive that "AIs' on-reflection values" are similar to "my on-reflection values". (Whereas the basic argument of my being similar to humans still work ok: "my on-reflection values" vs. "other humans' on-reflection values".)

Edit: Oops, I accidentally switched to talking about "my on-reflection values" rather than "total utilitarian values". The former is ultimately what I care more about, though, so it is what I'm more interested in. But sorry for the switch.

There might not be any real disagreement. I'm just saying that there's no direct conflict between "present people having material wealth beyond what they could possibly spend on themselves" and "virtually all resources are used in the way that totalist axiologies would recommend".

What's the argument for why an AI future will create lots of value by total utilitarian lights?

At least for hedonistic total utilitarianism, I expect that a large majority of expected-hedonistic-value (from our current epistemic state) will be created by people who are at least partially sympathetic to hedonistic utilitarianism or other value systems that value a similar type of happiness in a scope-sensitive fashion. And I'd guess that humans are more likely to have such values than AI systems. (At least conditional on my thinking that such values are a good idea, on reflection.)

Objective-list theories of welfare seems even less likely to be endorsed by AIs. (Since they seem pretty niche to human values.)

There's certainly some values you could have that would mainly be concerned that we got any old world with a large civilization. Or that would think it morally appropriate to be happy that someone got to use the universe for what they wanted, and morally inappropriate to be too opinionated about who that should be. But I don't think that looks like utilitarianism.

I find it plausible that future humans will choose to create much fewer minds than they could. But I don't think that "selfishly desiring high material welfare" will require this. Just the milky way has enough stars for each currently alive human to get an entire solar system each. Simultaneously, intergalactic colonization is probably possible (see here) and I think the stars in our own galaxy is less than 1-in-a-billion of all reachable stars. (Most of which are also very far away, which further contributes to them not being very interesting to use for selfish purposes.)

When we're talking about levels of consumption that are greater than a solar system, and that will only take place millions of years in the future, it seems like the relevant kind of human preferences to be looking at is something like "aesthetic" preference. And so I think the relevant analogies are less that of present humans optimizing for their material welfare, but perhaps more something like "people preferring the aesthetics of a clean and untouched universe (or something else: like the aesthetics of a universe used for mostly non-sentient art) over the aesthetics of a universe which is packed with joy".

I think your point "We may seek to rationalise the former [I personally don’t want to live in a large mediocre world, for self-interested reasons] as the more noble-seeming latter [desire for high average welfare]" is the kind of thing that might influence this aesthetic choice. Where "I personally don’t want to live in a large mediocre world, for self-interested reasons" would split into (i) "it feels bad to create a very unequal world where I have lots more resources than everyone else", and (ii) "it feels bad to massively reduce the amount of resources that I personally have, to that of the average resident in a universe packed full with life".

compared to MIRI people, or even someone like Christiano, you, or Joe Carlsmith probably have "low" estimates

Christiano says ~22% ("but you should treat these numbers as having 0.5 significant figures") without a time-bound; and Carlsmith says ">10%" (see bottom of abstract) by 2070. So no big difference there.

I'll hopefully soon make a follow-up post with somewhat more concrete projects that I think could be good. That might be helpful.

Are you more concerned that research won't have any important implications for anyone's actions, or that the people whose decisions ought to change as a result won't care about the research?

Similary, 'Politics is the Mind-Killer' might be the rationalist idea that has aged worst - especially for its influences on EA.

What influence are you thinking about? The position argued in the essay seems pretty measured.

Politics is an important domain to which we should individually apply our rationality—but it’s a terrible domain in which to learn rationality, or discuss rationality, unless all the discussants are already rational. [...]

I’m not saying that I think we should be apolitical, or even that we should adopt Wikipedia’s ideal of the Neutral Point of View. But try to resist getting in those good, solid digs if you can possibly avoid it. If your topic legitimately relates to attempts to ban evolution in school curricula, then go ahead and talk about it—but don’t blame it explicitly on the whole Republican Party; some of your readers may be Republicans, and they may feel that the problem is a few rogues, not the entire party.

I liked this recent interview with Mark Dybul who worked on PEPFAR from the start: https://www.statecraft.pub/p/saving-twenty-million-lives

One interesting contrast with the conclusion in this post is that Dybul thinks that PEPFAR's success was a direct consequence of how it didn't involve too many people and departments early on — because the negotiations would have been too drawn out and too many parties would have tried to get pieces of control. So maybe a transparent process that embraced complexity wouldn't have achieved much, in practice.

(At other parts in the process he leaned farther towards transparency than was standard — sharing a ton of information with congress.)

FWIW you can see more information, including some of the reasoning, on page 655 (# written on pdf) /  659 (# according to page searcher) of the report. (H/t Isabel.) See also page 214 for the definition of the question.

Some tidbits:

Experts started out much higher than superforecasters, but updated downwards after discussion. Superforecasters updated a bit upward, but less:

(Those are billions on the y-axis.)

This was surprising to me. I think the experts' predictions look too low even before updating, and look much worse after updating!

The part of the report that talks about "arguments given for lower forecasts". (The footnotes contain quotes from people expressing those views.)

Arguments given for lower forecasts (2024: <$40m, 2030: <$110m, 2050: ⩽$200m)

● Training costs have been stable around $10m for the last few years.1326

● Current trend increases are not sustainable for many more years.1327 One team cited this AI Impacts blog post.

● Major companies are cutting costs.1328

● Increases in model size and complexity will be offset by a combination of falling compute costs, pre-training, and algorithmic improvements.1329

● Large language models will probably see most attention in the near future, and these are bottlenecked by availability of data, which will lead to smaller models and less compute.1330

● Not all experiments will be public, and it is possible that the most expensive experiments will not be public.1331

(This last bullet point seems irrelevant to me. The question doesn't specify that the experiments has to be public, and "In the absence of an authoritative source, the question will be resolved by a panel of experts.")

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