↑ comment by Joe Carlsmith (joekc) ·
2021-05-07T17:52:24.058Z · LW(p) · GW(p)
Thanks for taking the time to clarify.
One other factor for me, beyond those you quote, is the “absolute” difficulty of ensuring practical PS-alignment, e.g. (from my discussion of premise 3):
Part of this uncertainty has to do with the “absolute” difficulty of achieving practical PS-alignment, granted that you can build APS systems at all. A system’s practical PS-alignment depends on the specific interaction between a number of variables -- notably, its capabilities (which could themselves be controlled/limited in various ways), its objectives (including the time horizon of the objectives in question), and the circumstances it will in fact exposed to (circumstances that could involve various physical constraints, monitoring mechanisms, and incentives, bolstered in power by difficult-to-anticipate future technology, including AI technology). I expect problems with proxies and search to make controlling objectives harder; and I expect barriers to understanding (along with adversarial dynamics, if they arise pre-deployment) to exacerbate difficulties more generally; but even so, it also seems possible to me that it won’t be “that hard” (by the time we can build APS systems at all) to eliminate many tendencies towards misaligned power-seeking (for example, it seems plausible to me that selecting very strongly against (observable) misaligned power-seeking during training goes a long way), conditional on retaining realistic levels of control over a system’s post-deployment capabilities and circumstances (though how often one can retain this control is a further question).
My sense is that relative to you, I am (a) less convinced that ensuring practical PS-alignment will be “hard” in this absolute sense, once you can build APS systems at all (my sense is that our conceptions of what it takes to “solve the alignment problem” might be different), (b) less convinced that practically PS-misaligned systems will be attractive to deploy despite their PS-misalignment (whether because of deception, or for other reasons), (c) less convinced that APS systems becoming possible/incentivized by 2035 implies “fast take-off” (it sounds like you’re partly thinking: those are worlds where something like the scaling hypothesis holds, and so you can just keep scaling up; but I don’t think the scaling hypothesis holding to an extent that makes some APS systems possible/financially feasible implies that you can just scale up quickly to systems that can perform at strongly superhuman levels on e.g. ~any task, whatever the time horizons, data requirements, etc), and (d) more optimistic about something-like-present-day-humanity’s ability to avoid/prevent failures at a scale that disempower ~all of humanity (though I do think Covid, and its policitization, an instructive example in this respect), especially given warning shots (and my guess is that we do get warning shots both before or after 2035, even if APS systems become possible/financially feasible before then).
Re: nuclear winter, as I understand it, you’re reading me as saying: “in general, if a possible and incentivized technology is dangerous, there will be warning shots of the dangers; humans (perhaps reacting to those warning shots) won’t deploy at a level that risks the permanent extinction/disempowerment of ~all humans; and if they start to move towards such disempowerment/extinction, they’ll take active steps to pull back.” And your argument is: “if you get to less than 10% doom on this basis, you’re going to give too low probabilities on scenarios like nuclear winter in the 20th century.”
I don’t think of myself as leaning heavily on an argument at that level of generality (though maybe there’s a bit of that). For example, that statement feels like it’s missing the “maybe ensuring practical PS-alignment just isn’t that hard, especially relative to building practically PS-misaligned systems that are at least superficially attractive to deploy” element of my own picture. And more generally, I expect to say different things about e.g. biorisk, climate change, nanotech, etc, depending on the specifics, even if generic considerations like “humans will try not to all die” apply to each.
Re: nuclear winter in particular, I’d want to think a bit more about what sort of probability I’d put on nuclear winter in the 20th century (one thing your own analysis skips is the probability that a large nuclear conflict injects enough smoke into the stratosphere to actually cause nuclear winter, which I don’t see as guaranteed -- and we’d need to specify what level of cooling counts). And nuclear winter on its own doesn’t include a “scaling to the permanent disempowerment/extinction of ~all of humanity” step -- a step that, FWIW, I see as highly questionable in the nuclear winter case, and which is important to my own probability on AI doom (see premise 5). And there are various other salient differences: for example, mutually assured destruction seems like a distinctly dangerous type of dynamic, which doesn’t apply to various AI deployment scenarios; nuclear weapons have widespread destruction as their explicit function, whereas most AI systems won’t; and so on. That said, I think comparisons in this vein could still be helpful; and I’m sympathetic to points in the vein of “looking at the history of e.g. climate, nuclear risk, BSL-4 accidents, etc the probability that humans will deploy technology that risks global catastrophe, and not stop doing so even after getting significant evidence about the risks at stake, can’t be that low” (I talk about this a bit in 4.4.3 and 6.2).