If anyone wants to have a voice chat with me about a topic that I'm interested in (see my recent post/comment history to get a sense), please contact me via PM.
My main "claims to fame":
I want to highlight a point I made in an EAF thread with Will MacAskill, which seems novel or at least underappreciated. For context, we're discussing whether the risk vs time (in AI pause/slowdown) curve is concave or convex, or in other words, whether the marginal value of an AI pause increases or decreases with pause length. Here's the whole comment for context, with the specific passage bolded:
Whereas it seems like maybe you think it's convex, such that smaller pauses or slowdowns do very little?
I think my point in the opening comment does not logically depend on whether the risk vs time (in pause/slowdown) curve is convex or concave[1], but it may be a major difference in how we're thinking about the situation, so thanks for surfacing this. In particular I see 3 large sources of convexity:
Like: putting in the schlep to RL AI and create scaffolds so that we can have AI making progress on these problems months earlier than we would have done otherwise
I think this kind of approach can backfire badly (especially given human overconfidence), because we currently don't know how to judge progress on these problems except by using human judgment, and it may be easier for AIs to game human judgment than to make real progress. (Researchers trying to use LLMs as RL judges apparently run into the analogous problem constantly.)
having governance set up such that the most important decision-makers are actually concerned about these issues and listening to the AI-results that are being produced
What if the leaders can't or shouldn't trust the AI results?
I'm trying to coordinate with, or avoid interfering with, people who are trying to implement an AI pause or create conditions conducive to a future pause. As mentioned in the grandparent comment, one way people like us could interfere with such efforts is by feeding into a human tendency to be overconfident about one's own ideas/solutions/approaches.
That fully boils down to whether the experience includes a preference to be dead (or to have not been born).
I'm pretty doubtful about this. It seems totally possible that evolution gave us a desire to be alive, while also gave us a net welfare that's negative. I mean we're deluded by default about a lot of other things (e.g., think there are agents/gods everywhere in nature, don't recognize that social status is a hugely important motivation behind everything we do), why not this too?
Let’s take an area where you have something to say, like philosophy. Would you be willing to outsource that?
Outsourcing philosophy is the main thing I've been trying to do, or trying to figure out how to safely do, for decades at this point. I've written about it in various places, including this post and my pinned tweet on X. Quoting from the latter:
Among my first reactions upon hearing "artificial superintelligence" were "I can finally get answers to my favorite philosophical problems" followed by "How do I make sure the ASI actually answers them correctly?"
Aside from wanting to outsource philosophy to ASI, I'd also love to have more humans who could answer these questions for me. I think about this a fair bit and wrote some things down but don't have any magic bullets.
(I currently think the best bet to eventually getting what I want is to encourage an AI pause along with genetic enhancements for human intelligence, have the enhanced humans solve metaphilosophy and other aspects of AI safety, then outsource the rest of philosophy to ASI, or have the enhanced humans decide what to do at that point.)
BTW I thought this would be a good test for how competent current AIs are at understanding someone's perspective so I asked a bunch of them how Wei Dai would answer your question, and all of them got it wrong on the first try, except Claude Sonnet 4.5 which got it right on the first try but wrong on the second try. It seems like having my public content in their training data isn't enough, and finding relevant info from the web and understanding nuance are still challenging for them. (GPT-5 essentially said I'd answer no because I wouldn't trust current AIs enough, which is really missing the point despite having this whole thread as context.)
By negative value I mean negative utility, or an experience that's worse than a neutral or null experience.
How do you come up with an encoding that covers all possible experiences? How do you determine which experiences have positive and negative values (and their amplitudes)? What to do about the degrees of freedom in choosing the Turing machine and encoding schemes, which can be handwaved away in some applications of AIT but not here I think?
Well, there's no point in asking the AI to make me good at things if I'm the kind of person who will just keep asking the AI to do more things for me!
But I'm only asking the AI to do things for me because they're too effortful or costly. If the AI made me good at these things with no extra effort or cost (versus asking the AI to do it) then why wouldn't I do them myself? For example I'm pretty sure I'd love the experience of playing like a concert pianist, and would ask for this ability, if doing so involved minimal effort and cost.
On the practical side, I agree that atrophy and being addicted/exploited are risks/costs worth keeping in mind, but I've generally made tradeoffs more in the direction of using shortcuts to minimize "doing chores" (e.g., buying a GPS for my car as soon as they came out, giving up learning an instrument very early) and haven't regretted it so far.
If my value system is only about receiving stuff from the universe, then the logical endpoint is a kind of blob that just receives stuff and doesn't even need a brain.
Unless one of the things you want to receive from the universe is to be like Leonardo da Vinci, or be able to do everything effortlessly and with extreme competence. Why "do chores" now if you can get to that endpoint either way, or maybe even more likely if you don't "do chores" because it allows you to save on opportunity costs and better deploy your comparative advantage? (I can understand if you enjoy the time spent doing these activities, but by calling them "chores" you seem to be implying that you don't?)
Hmm, I find it hard to understand or appreciate this attitude. I can't think of any chores that I intrinsically don't want to outsource, only concerns that I may not be able to trust the results. What are some other examples of chores you do and don't want to outsource? Do you have any pattern or explanation of where you draw the line? Do you think people who don't mind outsourcing all their chores are wrong in some way?
A clear mistake of early AI safety people is not emphasizing enough (or ignoring) the possibility that solving AI alignment (as a set of technical/philosophical problems) may not be feasible in the relevant time-frame, without a long AI pause. Some have subsequently changed their minds about pausing AI, but by not reflecting on and publicly acknowledging their initial mistakes, I think they are or will be partly responsible for others repeating similar mistakes.
Case in point is Will MacAskill's recent Effective altruism in the age of AGI. Here's my reply, copied from EA Forum:
I think it's likely that without a long (e.g. multi-decade) AI pause, one or more of these "non-takeover AI risks" can't be solved or reduced to an acceptable level. To be more specific:
I'm worried that by creating (or redirecting) a movement to solve these problems, without noting at an early stage that these problems may not be solvable in a relevant time-frame (without a long AI pause), it will feed into a human tendency to be overconfident about one's own ideas and solutions, and create a group of people whose identities, livelihoods, and social status are tied up with having (what they think are) good solutions or approaches to these problems, ultimately making it harder in the future to build consensus about the desirability of pausing AI development.
Strongly agree that metaethics is a problem that should be central to AI alignment, but is being neglected. I actually have a draft about this, which I guess I'll post here as a comment in case I don't get around to finishing it.
Metaethics and Metaphilosophy as AI Alignment's Central Philosophical Problems
I often talk about humans or AIs having to solve difficult philosophical problems as part of solving AI alignment, but what philosophical problems exactly? I'm afraid that some people might have gotten the impression that they're relatively "technical" problems (in other words, problems whose solutions we can largely see the shapes of, but need to work out the technical details) like anthropic reasoning and decision theory, which we might reasonably assume or hope that AIs can help us solve. I suspect this is because due to their relatively "technical" nature, they're discussed more often on LessWrong and AI Alignment Forum, unlike other equally or even more relevant philosophical problems, which are harder to grapple with or "attack". (I'm also worried that some are under the mistaken impression that we're closer to solving these "technical" problems than we actually are, but that's not the focus of the current post.)
To me, the really central problems of AI alignment are metaethics and metaphilosophy, because these problems are implicated in the core question of what it means for an AI to share a human's (or a group of humans') values, or what it means to help or empower a human (or group of humans). I think one way that the AI alignment community has avoided this issue (even those thinking about longer term problems or scalable solutions) is by assuming that the alignment target is someone like themselves, i.e. someone who clearly understands that they are and should be uncertain about what their values are or should be, or are at least willing to question their moral beliefs, and eager or at least willing to use careful philosophical reflection to solve their value confusion/uncertainty. To help or align to such a human, the AI perhaps doesn't need an immediate solution to metaethics and metaphilosophy, and can instead just empower the human in relatively commonsensical ways, like keeping them safe and gather resources for them, and allow them to work out their own values in a safe and productive environment.
But what about the rest of humanity who seemingly are not like that? From an earlier comment:
What are the real values of someone whose apparent values (stated and revealed preferences) can change in arbitrary and even extreme ways as they interact with other humans in ordinary life (i.e., not due to some extreme circumstances like physical brain damage or modification), and who doesn't care about careful philosophical inquiry? What does it mean to "help" someone like this? To answer this, we seemingly have to solve metaethics (generally understand the nature of values) and/or metaphilosophy (so the AI can "do philosophy" for the alignment target, "doing their homework" for them). The default alternative (assuming we solve other aspects of AI alignment) seems to be to still empower them in straightforward ways, and hope for the best. But I argue that giving people who are unreflective and prone to value drift god-like powers to reshape the universe and themselves could easily lead to catastrophic outcomes on par with takeover by unaligned AIs, since in both cases the universe becomes optimized for essentially random values.
A related social/epistemic problem is that unlike certain other areas of philosophy (such as decision theory and object-level moral philosophy), people including alignment researchers just seem more confident about their own preferred solution to metaethics, and comfortable assuming their own preferred solution is correct as part of solving other problems, like AI alignment or strategy. (E.g., moral anti-realism is true, therefore empowering humans in straightforward ways is fine as the alignment target can't be wrong about their own values.) This may also account for metaethics not being viewed as a central problem in AI alignment (i.e., some people think it's already solved).
I'm unsure about the root cause(s) of confidence/certainty in metaethics being relatively common in AI safety circles. (Maybe it's because in other areas of philosophy, the various proposed solutions are more obviously unfinished or problematic, e.g. the well-known problems with utilitarianism.) I've previously argued for metaethical confusion/uncertainty being normative at this point, and will also point out now that from a social perspective there is apparently wide disagreement about the problems among philosophers and alignment researchers, so how can it be right to assume some controversial solution to it (which every proposed solution is at this point) as part of a specific AI alignment or strategy idea?