We think it works like this
Who is “we”? Is it:
only you and your team?
the entire Apollo Research org?
the majority of mechinterp researchers worldwide?
some other group/category of people?
Also, this definitely deserves to be made into a high-level post, if you end up finding the time/energy/interest in making one.
randomly
As an aside (that’s still rather relevant, IMO), it is a huge pet peeve of mine when people use the word “randomly” in technical or semi-technical contexts (like this one) to mean “uniformly at random” instead of just “according to some probability distribution.” I think the former elevates and reifies a way-too-common confusion and draws attention away from the important upstream generator of disagreements, namely how exactly the constitution is sampled.
I wouldn’t normally have said this, but given your obvious interest in math, it’s worth pointing out that the answers to these questions you have raised naturally depend very heavily on what distribution we would be drawing from. If we are talking about, again, a uniform distribution from “the design space of minds-in-general” (so we are just summoning a “random” demon or shoggoth), then we might expect one answer. If, however, the search is inherently biased towards a particular submanifold of that space, because of the very nature of how these AIs are trained/fine-tuned/analyzed/etc., then you could expect a different answer.
One of the advantages to remaining agnostic comes from the same argument that users put forth in the comment sections on this very site way back in the age of the Sequences (I can look up the specific links if people really want me to, they were in response to the Doublethink Sequence) for why it’s not necessarily instrumentally rational for limited beings like humans to actually believe in the Litany of Tarski: if you are in a precarious social situation, in which retaining status/support/friends/resources is contingent on you successfully signaling to your in-group that you maintain faith in their core teachings, it simply doesn’t suffice to say “acquire all the private truth through regular means and don’t talk/signal publicly the stuff that would be most dangerous to you,” because you don’t get complete control over what you signal.
If you learn that the in-group is wrong about some critical matter, and you understand that in-group members realizing you no longer agree with them will result in harm to you (directly, or through your resources being cut off), your only option is, to act (to some extent) deceptively. To take on the role, QuirrellMort-style, of somebody who does not have access to the information you have actually stumbled upon, and to pretend to be just another happy & clueless member of the community.
This is capital-H Hard. Lying (or even something smaller-scale like lesser deceptions), when done consistently and routinely, to people that you consider(ed) your family/friends/acquaintances, is very hard for (the vast majority of) people. For straightforward evolutionary reasons, we have evolved to be really good at detecting when one of our own is not being fully forthcoming. You can bypass this obstacle if the number of interactions you have is small, or if, as is usually the case in modern life when people get away with lies, nobody actually cares about the lie and it’s all just a game of make-believe where you just have to “utter the magic words.” But when it’s not a game, when people do care about honestly signaling your continued adherence to the group’s beliefs and epistemology, you’re in big trouble.
Indeed, by far the most efficient way of convincing others of your bullshit on a regular basis is to convince yourself first, and by putting yourself in a position where you must do the former, you are increasing the likelihood of the latter with every passing day. Quite the opposite of what you’d like to see happen, if you are about truth-seeking to any large extent.
(addendum: admittedly, this doesn’t answer the question fully, since it doesn’t deal with the critical distinction between agnosticism and explicit advocacy, but I think it does get at something reasonably important in the vicinity of it anyway)
There’s an alignment-related problem, the problem of defining real objects. Relevant topics: environmental goals; task identification problem; “look where I’m pointing, not at my finger”; Eliciting Latent Knowledge.
Another highly relevant post: The Pointers Problem.
So, where are the Knuths of the modern era? Why is modern AI dominated by the Lorem Epsoms of the world? Where is the craftsmanship? Why are our AI tools optimized for seeming good, rather than being good?
[2] Remember back in 2013 when the talk of the town was how vector representations of words learned by neural networks represent rich semantic information? So you could do cool things like take the [male] vector, subtract the [female] vector, add the [king] vector, and get out something close to the [queen] vector? That was cool! Where’s the stuff like that these days?
I’m a bit confused by your confusion, and by the fact that your post does not contain what seems to me like the most straightforward explanation of these phenomena. An explanation that I am almost fully certain you are aware of, and which seems to be almost universally agreed upon by those interested (at any level) in interpretability in ML.
Namely the fact that, starting in the 2010s, it happened to be the case (for a ton of historically contingent reasons) that top AI companies (at the beginning, and followed by other ML hubs and researchers afterwards) realized the bitter lesson is basically correct: attempts to hard-code human knowledge or intuition into frontier models ultimately always harm their performance in the long-term compared to “literally just scale the model with more data and compute.” This led to a focus, among experts and top engineers, on figuring out scaling laws, ways of improving the quality and availability of data (perhaps through synthetic generation methods), ways of creating better end-user products through stuff like fine-tuning and RLHF, etc, instead of the older GOFAI stuff of trying to figure out at a deeper level what is going on inside the model.
Another way of saying this is that top researchers and companies ultimately stumbled on an AI paradigm which increased capabilities significantly more than had been achievable previously, but at the cost of strongly decoupling “capability improvements” and “interpretability improvements” as distinct things that researchers and engineers could focus on. It’s not that capability and interpretability were necessarily tightly correlated in the past; that is not the claim I am making. Rather, I am saying that in the pre-(transformer + RL) era, the way you generated improvements in your models/AI was by figuring out specific issues and analyzing them deeply to find out how to get around them, whereas now, a far simpler, easier, less insight-intensive approach became available: literally just scaling up the model with more data and compute.
So the basic point is that you no longer see all this cool research on the internal representations that models generate of high-dimensional data like word embeddings (such as the word2vec stuff you are referring to in the second footnote) because you no longer have nearly as much of a need for these insights in order to improve the capabilities/performance of the AI tools currently in use. It’s fundamentally an issue with demand, not with supply. And the demand from the interpretability-focused AI alignment community is just nowhere close to large enough to bridge the gap and cover the loss generated by the shift in paradigm focus and priorities among the capabilities/”normie” AI research community.
Indeed, the notion that nowadays, the reason you no longer have deep thinkers who try to figure out what is going on or are “motivated by reasons” in how they approach these issues, is somehow because “careful thinkers read LessWrong and decided against contributing to AI progress,” seems… rather ridiculous to me? It’s not like I enjoy responding to an important question that you are asking with derision in lieu of a substantive response, but… I mean, the literal authors of the word2vec paper you cited were AI (capabilities) researchers working at top companies, not AI alignment researchers! Sure, some people like Bengio and Hofstadter (less relevant in practical terms) who are obviously not “LARP-ing impostors” in Wentworth’s terminology have made the shift from capabilities work to trying to raise public awareness of alignment/safety/control problems. But the vast majority (according to personal experience, general impressions, as well as the current state of the discourse on these topics) absolutely have not, and since they were the ones generating the clever insights back in the day, of course it makes sense that the overall supply of these insights has gone down.
I just really don’t see how it could be the case that “people refuse to generate these insights because they have been convinced by AI safety advocates that it would dangerously increase capabilities and shorten timelines” and “people no longer generate these insights as much because they are instead focusing on other tasks that improve model capabilities more rapidly and robustly, given the shifted paradigm” are two hypotheses that can be given similar probabilities in any reasonable person’s mind. The latter should be at least a few orders of magnitude more likely than the former, as I see it.
some people say that “winning is about not playing dominated strategies”
I do not believe this statement. As in, I do not currently know of a single person, associated either with LW or with decision-theory academia, that says “not playing dominated strategies is entirely action-guiding.” So, as Raemon pointed out, “this post seems like it’s arguing with someone but I’m not sure who.”
In general, I tend to mildly disapprove of words like “a widely-used strategy”, “we often encounter claims” etc, without any direct citations to the individuals who are purportedly making these mistakes. If it really was that widely-used, surely it would be trivial for the authors to quote a few examples off the top of their head, no? What does it say about them that they didn’t?
I think it’s not quite as clear as needing to shut down all other AGI projects or we’re doomed; a small number of AGIs under control of different humans might be stable with good communication and agreements, at least until someone malevolent or foolish enough gets involved.
Realistically, in order to have a reasonable degree of certainty that this state can be maintained for more than a trivial amount of time, this would, at the very least, require a hard ban on open-source AI, as well as international agreements to strictly enforce transparency and compute restrictions, with the direct use of force if need be, especially if governments get much more involved in AI in the near-term future (which I expect will happen).
Do you agree with this, as a baseline?
Does this plan necessarily factor through the using the intent-aligned AGI to quickly commit some sort of pivotal act that flips the gameboard and prevents other intent-aligned AGIs from being used malevolently by self-interested or destructive (human) actors to gain a decisive strategic advantage? After all, it sure seems less than ideal to find yourself in a position where you can solve the theoretical parts of value alignment,[1] but you cannot implement that in practice because control over the entire future light cone has already been permanently taken over by an AGI intent-aligned to someone who does not care about any of your broadly prosocial goals...
In so far as something like this even makes sense, which I have already expressed my skepticism of many times, but I don’t think I particularly want to rehash this discussion with you right now...
You’ve gotten a fair number of disagree-votes thus far, but I think it’s generally correct to say that many (arguably most) prediction markets still currently lack the trading volume necessary to justify confidence that EMH-style arguments mean inefficiencies will be rapidly corrected. To a large extent, it’s fair to say this is due to over-regulation and attempts at outright banning (perhaps the relatively recent 5th Circuit ruling in favor of PredictIt against the Commodities Future Trading Commission is worth looking at as a microcosm of how these legal battles are playing out in today’s day and age).
Nevertheless, the standard theoretical argument that inefficiencies in prediction markets are exploitable and thus lead to a self-correcting mechanism still seems entirely correct, as Garrett Baker points out.
I think mind projection especially happens with value judgements—i.e. people treat “goodness” or “badness” as properties of things out in the world.
It’s worth noting, I think, that Steve Byrnes has done a great job describing and analyzing this phenomenon in Section 2.2 of his post on Valence & Normativity. I have mentioned before that I think his post is excellent, so it seems worthwhile to signal-boost it here as well.
Cognitively speaking, treating value as a property of stuff in the world can be useful for planning
Also mentioned and analyzed in Section 2.3 of Byrnes’s post :)
Another option is to move to the Platinum Rule: Treat others the way they would want to be treated.
This suffers from a different, but still very serious problem, namely the fact that most people are at least somewhat selfish and want to be treated in a way that gives them (from an overall societal perspective) an unjustifiably large amount of resources, priority, respect, epistemic authority, etc. Granting them this might be good for the individuals in those spots, but has a negative effect on society as a whole.
It sure would be nice and convenient if it just so happened that “do what person X tells you to” and “do what’s best for the community around you” were always in alignment. After all, in such a world, we wouldn’t need to make these tough choices or ever have to reject the requests made by concrete people in front of us because of abstract principles or consequentialist reasoning (which is often quite difficult to do, especially for otherwise nice, prosocial, and empathetic people). But, as it turns out, we live in a world with scarce resources, one in which avoiding conflict by taking a third option often fails, and we must confront the issues directly instead.
For example, if somebody tells you that the way they want you to treat them is to always agree with everything they are saying and to never criticize their statements, what are you meant to do? If you give in, this not only allows potentially bad and damaging claims to go unchallenged, but also sets up terrible incentives for everyone else to copy this behavior. But if you don’t give in, suddenly you aren’t using the Platinum Rule anymore; perhaps you have some set of principles that tell you where to draw the line between “spots where people are allowed to impose their desires for how they should be treated on you” and “spots where such requests should be given no deference whatsoever,” but now you’ve just moved the entire discussion up a step without major changes to the status quo; everyone will start arguing over where the line should be drawn and which side of it any given situation falls on.
There is also another issue, namely that if you empower individuals to affect great change in how others interact with them solely on the basis of their preferences, you are setting up bad incentives for how those individuals’ preferences will change over time. As Vladimir_M has written in a classic response[1] to Scott Alexander’s old post:
In a world where people make decisions according to this principle, one has the incentive to self-modify into a utility monster who feels enormous suffering at any actions of other people one dislikes for whatever reason. And indeed, we can see this happening to some extent: when people take unreasonable offense and create drama to gain concessions, their feelings are usually quite sincere.
You say, “pretending to be offended for personal gain is… less common in reality than it is in people’s imaginations.” That is indeed true, but only because people have the ability to whip themselves into a very sincere feeling of offense given the incentive to do so. Although sincere, these feelings will usually subside if they realize that nothing’s to be gained.
And then the follow-up:
If we have a dispute and I credibly signal that I’m going to flip out and create drama out of all proportion to the issue at stake, you’re faced with a choice between conceding to my demands or getting into an unpleasant situation that will cost more than the matter of dispute is worth. I’m sure you can think of many examples where people successfully get the upper hand in disputes using this strategy. The only way to disincentivize such behavior is to pre-commit credibly to be defiant in face of threats of drama. In contrast, if you act like a (naive) utilitarian, you are exceptionally vulnerable to this strategy, since I don’t even need drama to get what I want, if I can self-modify to care tremendously about every single thing I want. (Which I won’t do if I’m a good naive utilitarian myself, but the whole point is that it’s not a stable strategy.)
Now, the key point is that such behavior is usually not consciously manipulative and calculated. On the contrary—someone flipping out and creating drama for a seemingly trivial reason is likely to be under God-honest severe distress, feeling genuine pain of offense and injustice. This is a common pattern in human social behavior: humans are extremely good at detecting faked emotions and conscious manipulation, and as a result, we have evolved so that our brains lash out with honest strong emotion that is nevertheless directed by some module that performs game-theoretic assessment of the situation. This of course prompts strategic responses from others, leading to a strategic arms race without end.
The further crucial point is that these game-theoretic calculators in our brains are usually smart enough to assess whether the flipping out strategy is likely to be successful, given what might be expected in response. Basically, it is a part of the human brain that responds to rational incentives even though it’s not under the control of the conscious mind. With this in mind, you can resolve the seeming contradiction between the sincerity of the pain of offense and the fact that it responds to rational incentives.
And not to get in the weeds of political issues too much, but I think the claims in his comment have been shown to be correct, given changes in social and political discourse in the US, at least, in the past 10 years or so.
Ben Pace has said that perhaps he doesn’t disagree with you in particular about this, but I sure think I do.[1]
I think the amount of stress incurred when doing public communication is nearly orthogonal to these factors, and in particular is, when trying to be as careful about anything as Zac is trying to be about confidentiality, quite high at baseline.
I don’t see how the first half of this could be correct, and while the second half could be true, it doesn’t seem to me to offer meaningful support for the first half either (instead, it seems rather… off-topic).
As a general matter, even if it were the case that no matter what you say, at least one person will actively misinterpret your words, this fact would have little bearing on whether you can causally influence the proportion of readers/community members that end up with (what seem to you like) the correct takeaways from a discussion of that kind.
Moreover, in a spot where you have something meaningful and responsible, etc, that you and your company have done to deal with safety issues, the major concern in your mind when communicating publicly is figuring out how to make it clear to everyone that you are on top of things without revealing confidential information. That is certainly stressful, but much less so than the additional constraint you have in a world in which you do not have anything concrete that you can back your generic claims of responsibility with, since that is a spot where you can no longer fall back on (a partial version of) the truth as your defense. For the vast majority of human beings, lying and intentional obfuscation with the intent to mislead are significantly more psychologically straining than telling the truth as-you-see-it is.
Overall, I also think I disagree about the amount of stress that would be caused by conversations with AI safety community members. As I have said earlier:
AI safety community members are not actually arbitrarily intelligent Machiavellians with the ability to convincingly twist every (in-reality) success story into an (in-perception) irresponsible gaffe;[1] the extent to which they can do this depends very heavily on the extent to which you have anything substantive to bring up in the first place.
[1] Quite the opposite, actually, if the change in the wider society’s opinions about EA in the wake of the SBF scandal is any representative indication of how the rationalist/EA/AI safety cluster typically handles PR stuff.
In any case, I have already made all these points in a number of ways in my previous response to you (which you haven’t addressed, and which still seem to me to be entirely correct).
He also said that he thinks your perspective makes sense, which… I’m not really sure about.
Definitely not trying to put words in Habryka’s mouth, but I did want to make a concrete prediction to test my understanding of his position; I expect he will say that:
the only work which is relevant is the one that tries to directly tackle what Nate Soares described as “the hard bits of the alignment challenge” (the identity of which Habryka basically agrees with Soares about)
nobody is fully on the ball yet
but agent foundations-like research by MIRI-aligned or formerly MIRI-aligned people (Vanessa Kosoy, Abram Demski, etc.) is the one that’s most relevant, in theory
however, in practice, even that is kinda irrelevant because timelines are short and that work is going along too slowly to be useful even for deconfusion purposes
Edit: I was wrong.
Updatelessness sure seems nice from a theoretical perspective, but it has a ton of problems that go beyond what you just mentioned and which seem to me to basically doom the entire enterprise (at least with regards to what we are currently discussing, namely people):
I am not aware of any method of operationalizing even a weak version of updatelessness in the context of cognitively limited human beings that do not have access to their own source code
I am pretty sure that a large portion of my values (and, by extension, the values of the vast majority of people) are indexical in nature, at least partly because my access to the outside world is mediated through sense data, which my S1 seems to value “terminally” and not as a mere proxy for preferences over current world-states. Indexicality seems to me to play very poorly with updatelesness (although I suspect you would know more about this than me, given your work in this area?)
I don’t currently know of a way that humans can remain updateless even under (what seems to be like an inordinately optimistic) world in which we can actually access the “source code” by figuring out how to model the abstract classical computation performed by a particular (and reified) subset of the brain’s electronic circuit, basically because of the reasons I gave in my comment to Wei Dai that I referenced earlier (“The feedback loops implicit in the structure of the brain cause reward and punishment signals to “release chemicals that induce the brain to rearrange itself” in a manner closely analogous to and clearly reminiscent of a continuous and (until death) never-ending micro-scale brain surgery. To be sure, barring serious brain trauma, these are typically small-scale changes, but they nevertheless fundamentally modify the connections in the brain and thus the computation it would produce in something like an emulated state (as a straightforward corollary, how would an em that does not “update” its brain chemistry the same way that a biological being does be “human” in any decision-relevant way?”)
I have a much broader skepticism about whether the concepts of “beliefs” and “values” make sense as distinct, coherent concepts that carve reality at the joints, and which I think is reflected in some of the other points I made in my long list of questions and confusions about these matters. It doesn’t really seem to me like updatelessness solves this, or even necessarily offers a concrete path forward on it.
Of course, I don’t expect that you are trying to literally say that going updateless gets rid of all the issues, but rather that thinking about it in those terms, after internalizing that perspective, helps put us in the right frame of mind to make progress on these philosophical and metaphilosophical matters moving forward. But, as I said at the end of my comment to Wei Dai:
I do not have answers to the very large set of questions I have asked and referenced in this comment. Far more worryingly, I have no real idea of how to even go about answering them or what framework to use or what paradigm to think through. Unfortunately, getting all this right seems very important if we want to get to a great future. Based on my reading of the general pessimism you have been signaling throughout your recent posts and comments, it doesn’t seem like you have answers to (or even a great path forward on) these questions either despite your great interest in and effort spent on them, which bodes quite terribly for the rest of us.
Perhaps if a group of really smart philosophy-inclined people who have internalized the lessons of the Sequences without being wedded to the very specific set of conclusions MIRI has reached about what AGI cognition must be like and which seem to be contradicted by the modularity, lack of agentic activity, moderate effectiveness of RLHF etc (overall just the empirical information) coming from recent SOTA models were to be given a ton of funding and access and 10 years to work on this problem as part of a proto-Long Reflection, something interesting would come out. But that is quite a long stretch at this point.
OK, but what is your “intent”? Presumably, it’s that something be done in accordance with your values-on-reflection, right?
No, I don’t think so at all. Pretty much the opposite, actually; if it was in accordance to my values-on-reflection, it would be value-aligned to me rather than intent-aligned. Collapsing the meaning of the latter into the former seems entirely unwise to me. After all, when I talk about my intent, I am explicitly not thinking about any long reflection process that gets at the “core” of my beliefs or anything like that;[1] I am talking more about something like this:
I have preferences right now; this statement makes sense in the type of low-specificity conversation dominated by intuition where we talk about such words as though they referred to real concepts that point to specific areas of reality. Those preferences are probably not coherent, in the case that I can probably be money pumped by an intelligent enough agent that sets up a strange-to-my-current-self scenario. But they still exist, and one of them is to maintain a sufficient amount of money in my bank account to continue living a relatively high-quality life. Whether I “endorse” those preferences or not is entirely irrelevant to whether I have them right now; perhaps you could offer a rational argument to eventually convince me that you would make much better use of all my money, and then I would endorse giving you that money, but I don’t care about any of that right now. My current, unreflectively-endorsed self, doesn’t want to part with what’s in my bank account, and that’s what guiding my actions, not an idealized, reified future version.
None of this means anything conclusive about me ultimately endorsing these preferences in the reflective limit, of those preferences being stable under ontology shifts that reveal how my current ontology is hopelessly confused and reifies the analogues of ghosts, of there being any nonzero intersection between the end states of a process that tries to find my individual volition, of changes to my physical and neurological make-up keeping my identity the same (in a decision-relevant sense relative to my values) when my memories and path through history change.
In any case, I am very skeptical of this whole values-on-reflection business,[2] as I have written about at length in many different spots (1, 2, 3 come to mind off the top of my head). I am loathe to keep copying the exposition of the same ideas over and over and over again (it also probably gets annoying to read at some point), but here is a relevant sample:
Whenever I see discourse about the values or preferences of beings embedded in a physical universe that goes beyond the boundaries of the domains (namely, low-specificity conversations dominated by intuition) in which such ultimately fake frameworks function reasonably well, I get nervous and confused. I get particularly nervous if the people participating in the discussions are not themselves confused about these matters (I am not referring to [Wei Dai] in particular here, since [Wei Dai] has already signaled an appropriate level of confusion about this). Such conversations stretch our intuitive notions past their breaking point by trying to generalize them out of distribution without the appropriate level of rigor and care.
What counts as human “preferences”? Are these utility function-like orderings of future world states, or are they ultimately about universe-histories, or maybe a combination of those, or maybe something else entirely? Do we actually have any good reason to think that (some form of) utility maximization explains real-world behavior, or are the conclusions broadly converged upon on LW ultimately a result of intuitions about what powerful cognition must be like whose source is a set of coherence arguments that do not stretch as far as they were purported to? What do we do with the fact that humans don’t seem to have utility functions and yet lingering confusion about this remained as a result of many incorrect and misleading statements by influential members of the community?
How can we use such large sample spaces when it becomes impossible for limited beings like humans or even AGI to differentiate between those outcomes and their associated events? After all, while we might want an AI to push the world towards a desirable state instead of just misleading us into thinking it has done so, how is it possible for humans (or any other cognitively limited agents) to assign a different value, and thus a different preference ranking, to outcomes that they (even in theory) cannot differentiate (either on the basis of sense data or through thought)?
In any case, are they indexical or not? If we are supposed to think about preferences in terms of revealed preferences only, what does this mean in a universe (or an Everett branch, if you subscribe to that particular interpretation of QM) that is deterministic? Aren’t preferences thought of as being about possible worlds, so they would fundamentally need to be parts of the map as opposed to the actual territory, meaning we would need some canonical framework of translating the incoherent and yet supposedly very complex and multidimensional set of human desires into something that actually corresponds to reality? What additional structure must be grafted upon the empirically-observable behaviors in order for “what the human actually wants” to be well-defined?
[...]
What do we mean by morality as fixed computation in the context of human beings who are decidedly not fixed and whose moral development through time is almost certainly so path-dependent (through sensitivity to butterfly effects and order dependence) that a concept like “CEV” probably doesn’t make sense? The feedback loops implicit in the structure of the brain cause reward and punishment signals to “release chemicals that induce the brain to rearrange itself” in a manner closely analogous to and clearly reminiscent of a continuous and (until death) never-ending micro-scale brain surgery. To be sure, barring serious brain trauma, these are typically small-scale changes, but they nevertheless fundamentally modify the connections in the brain and thus the computation it would produce in something like an emulated state (as a straightforward corollary, how would an em that does not “update” its brain chemistry the same way that a biological being does be “human” in any decision-relevant way?).
I do have some other thoughts on other parts of the post, which I might write out at some point.
I don’t really think any of that affects the difficulty of public communication
The basic point would be that it’s hard to write publicly about how you are taking responsible steps that grapple directly with the real issues… if you are not in fact doing those responsible things in the first place. This seems locally valid to me; you may disagree on the object level about whether Adam Scholl’s characterization of Anthropic’s agenda/internal work is correct, but if it is, then it would certainly affect the difficulty of public communication to such an extent that it might well become the primary factor that needs to be discussed in this matter.
Indeed, the suggestion is for Anthropic employees to “talk about their views (on AI progress and risk and what Anthropic is doing and what Anthropic should do) with people outside Anthropic” and the counterargument is that doing so would be nice in an ideal world, except it’s very psychologically exhausting because every public statement you make is likely to get maliciously interpreted by those who will use it to argue that your company is irresponsible. In this situation, there is a straightforward direct correlation between the difficulty of public communication and the likelihood that your statements will get you and your company in trouble.
But the more responsible you are in your actual work, the more responsible-looking details you will be able to bring up in conversations with others when you discuss said work. AI safety community members are not actually arbitrarily intelligent Machiavellians with the ability to convincingly twist every (in-reality) success story into an (in-perception) irresponsible gaffe;[1] the extent to which they can do this depends very heavily on the extent to which you have anything substantive to bring up in the first place. After all, as Paul Graham often says, “If you want to convince people of something, it’s much easier if it’s true.”
As I see it, not being able to bring up Anthropic’s work/views on this matter without some AI safety person successfully making it seem like Anthropic is behaving badly is rather strong Bayesian evidence that Anthropic is in fact behaving badly. So this entire discussion, far from being an insult, seems directly on point to the topic at hand, and locally valid to boot (although not necessarily sound, as that depends on an individualized assessment of the particular object-level claims about the usefulness of the company’s safety team).
Quite the opposite, actually, if the change in the wider society’s opinions about EA in the wake of the SBF scandal is any representative indication of how the rationalist/EA/AI safety cluster typically handles PR stuff.
Ah, oops.
I think “The first AGI probably won’t perform a pivotal act” is by far the weakest section.
To start things off, I would predict a world with slow takeoff and personal intent-alignment looks far more multipolar than the standard Yudkowskian recursively self-improving singleton that takes over the entire lightcone in a matter of “weeks or hours rather than years or decades”. So the title of that section seems a bit off because, in this world, what the literal first AGI does becomes much less important, since we expect to see other similarly capable AI systems get developed by other leading labs relatively soon afterwards anyway.
But, in any case, the bigger issue I have with the reasoning there is the assumption (inferred from statements like “the humans in charge of AGI may not have the chutzpah to even try such a thing”) that the social response to the development of general intelligence is going to be… basically muted? Or that society will continue to be business-as-normal in any meaningful sense? I would be entirely shocked if the current state of the world in which the vast majority of people have little knowledge of the current capabilities of AI systems and are totally clueless about the AI labs’ race towards AGI were to continue past the point that actual AGI is reached.
I think intuitions of the type that “There’s No Fire Alarm for Artificial General Intelligence” are very heavily built around the notion of rapid takeoff that is so fast there might well be no major economic evidence of the impact of AI before the most advanced systems become massively superintelligent. Or that there might not be massive rises in unemployment negatively impacting many people who are trying to live through the transition to an eventual post-scarcity economy. Or that the ways people relate to AIs or to one another will not be completely turned on their heads.
A future world in which we get pretty far along the way to no longer needing old OSs or programming languages because you can get an LLM to write really good code for you, in which AI can write an essay better than most (if not all) A+ undergrad students, in which it can solve Olympiad math problems better than all contestants and do research better than a graduate student, in which deep-learning based lie detection technology actually gets good and starts being used more and more, in which major presidential candidates are already using AI-generated imagery and causing controversies over whether others are using similar technology, in which the capacity to easily generate whatever garbage you request breaks the internet or fills it entirely with creepy AI-generated propaganda videos made by state-backed cults, is a world in which stability and equilibrium are broken. It is not a world in which “normality” can continue, in the sense that governments and people keep sleepwalking through the threat posed by AI.
I consider it very unlikely that such major changes to society can go by without the fundamental thinking around them changing massively, and without those who will be close to the top of the line of “most informed about the capabilities of AI” grasping the importance of the moment. Humans are social creatures who delegate most of their thinking on what issues should even be sanely considered to the social group around them; a world with slow takeoff is a world in which I expect massive changes to happen during a long enough time-span that public opinion shifts, dragging along with it both the Overton window and the baseline assumptions about what can/must be done about this.
There will, of course, be a ton of complicating factors that we can discuss, such as the development of more powerful persuasive AI catalyzing the shift of the world towards insanity and inadequacy, but overall I do not expect the argument in this section to follow through.
Right, but such an argument would not be “sound” from a theoretical logical perspective (according to the definition I mentioned in my previous comment), which is the only point I meant to get across earlier.
[Coming at this a few months late, sorry. This comment by @Steven Byrnes sparked my interest in this topic once again]
Ngl, I find everything you’re written here a bit… baffling, Seth. Your writing in particular and your exposition of your thoughts on AI risk generally does not use evolutionary analogies, but this only means that posts and comments criticizing analogies with evolution (sample: 1, 2, 3, 4, 5, etc) are just not aimed at you and your reasoning. I greatly enjoy reading your writing and pondering the insights you bring up, but you are simply not even close to the most publicly-salient proponent of “somewhat high P(doom)” among the AI alignment community. It makes perfect sense from the perspective of those who disagree with you (or other, more hardcore “doomers”) on the bottom-line question of AI to focus their public discourse primarily on responding to the arguments brought up by the subset of “doomers” who are most salient and also most extreme in their views, namely the MIRI-cluster centered around Eliezer, Nate Soares, and Rob Bensinger.
And when you turn to MIRI and the views that its members have espoused on these topics, I am very surprised to hear that “The arguments for misgeneralization/mis-specification stand on their own” and are not ultimately based on analogies with evolution.
But anyway, to hopefully settle this once and for all, let’s go through all the examples that pop up in my head immediately when I think of this, shall we?
From the section on inner & outer alignment of “AGI Ruin: A List of Lethalities”, by Yudkowsky (I have removed the original emphasis and added my own):
From “A central AI alignment problem: capabilities generalization, and the sharp left turn”, by Nate Soares, which, by the way, quite literally uses the exact phrase “The central analogy”; as before, emphasis is mine:
From “The basic reasons I expect AGI ruin”, by Rob Bensinger:
From “Niceness is unnatural”, by Nate Soares:
From “Superintelligent AI is necessary for an amazing future, but far from sufficient”, by Nate Soares:
From the Eliezer-edited summary of “Ngo and Yudkowsky on alignment difficulty”, by… Ngo and Yudkowsky:
From “Comments on Carlsmith’s “Is power-seeking AI an existential risk?”″, by Nate Soares:
From “Soares, Tallinn, and Yudkowsky discuss AGI cognition”, by… well, you get the point:
From “Humans aren’t fitness maximizers”, by Soares:
From “Shah and Yudkowsky on alignment failures”, by the usual suspects:
From the comments on “Late 2021 MIRI Conversations: AMA / Discussion”, by Yudkowsky:
From Yudkowsky’s appearance on the Bankless podcast (full transcript here):
At this point, I’m tired, so I’m logging off. But I would bet a lot of money that I can find at least 3x the number of these examples if I had the energy to. As Alex Turner put it, it seems clear to me that, for a very high portion of “classic” alignment arguments about inner & outer alignment problems, at least in the form espoused by MIRI, the argumentative bedrock is ultimately based on little more than analogies with evolution.