The post seems to be talking about these topics solely from the perspective of the relation between the individual and the community they belong to ("You are a member of some community", emphasis added). But, in my opinion, one of the most important manifestations of guilt (and shame, etc) to analyze, if we aim to understand these emotions more deeply, is when the individual feels guilty for violating a norm inside a community they are no longer a part of. This comes about because the vast majority of people have a tendency to internalize the norms and lessons they are taught and to try to uphold them regardless of the external incentives they face from the group.

As Eliezer once wrote, when you punish a child for stealing cookies, the child learns not to be caught stealing, but usually and to some extent, they also learn not to steal, as an end goal/principle independent of whether they get caught.

I'm wary of a possible equivocation about what the "natural abstraction hypothesis" means here.

If we are referring to the redundant information hypothesis and various kinds of selection theorems, this is a mathematical framework that could end up being correct, is not at all ungrounded, and Wentworth sure seems like the man for the job. 

But then you are still left with the task of grounding this framework in physical reality to allow you to make correct empirical predictions about and real-world interventions on what you will see from more advanced models. Our physical world abstracting well seems plausible (not necessarily >50% likely), and these abstractions being "natural" (e.g., in a category-theoretic sense) seems likely conditional on the first clause of this sentence being true, but I give an extremely low probability to the idea that these abstractions will be used by any given general intelligence or (more to the point) advanced AI model to a large and wide enough extent that retargeting the search is even close to possible.

And indeed, it is the latter question that represents the make-or-break moment for natural abstractions' theory of change, for it is only when the model in front of you (as opposed to some other idealized model) uses these specific abstractions that you can look through the AI's internal concepts and find your desired alignment target.

Rohin Shah has already explained the basic reasons why I believe the mesa-optimizer-type search probably won't exist/be findable in the inner workings of the models we encounter: "Search is computationally inefficient relative to heuristics, and we'll be selecting really hard on computational efficiency." And indeed, when I look at the only general intelligences I have ever encountered in my entire existence thus far, namely humans, I see mostly just a kludge of impulses and heuristics that depend very strongly (almost entirely) on our specific architectural make-up and the contextual feedback we encounter in our path through life. Change either of those and the end result shifts massively.

And even moving beyond that, is the concept of the number "three" a natural abstraction? Then I see entire collections and societies of (generally intelligent) human beings today who don't adopt it. Are the notions of "pressure" and "temperature" and "entropy" natural abstractions? I look at all human beings in 1600 and note that not a single one of them had ever correctly conceptualized a formal version of any of those; and indeed, even making a conservative estimate of the human species (with an essentially unchanged modern cognitive architecture) having existed for 200k years, this means that for 99.8% of our species' history, we had no understanding whatsoever of concepts as "universal" and "natural" as that. If you look at subatomic particles like electrons or stuff in quantum mechanics, the percentage manages to get even higher. And that's only conditioning on abstractions about the outside world that we have eventually managed to figure out; what about the other unknown unknowns?

For example, this post does an experiment that shows that OOD data still makes the Platonic Representation Hypothesis true, meaning that it's likely that deeper factors are at play than just shallow similarity

I don't think it shows that at all, since I have not been able to find any analysis of the methodology, data generation, discussion of results, etc. With no disrespect to the author (who surely wasn't intending for his post to be taken as authoritative as a full paper in terms of updating towards his claim), this is shoddy science, or rather not science at all, just a context-free correlation matrix.

Anyway, all this is probably more fit for a longer discussion at some point.

(Prefatory disclaimer that, admittedly as an outsider to this field, I absolutely disagree with the labeling of prosaic AI work as useless streetlighting, for reasons building upon what many commenters wrote in response to the very posts you linked here as assumed background material. But in the spirit of your post, I shall ignore that moving forward.)

The "What to Do About It" section dances around but doesn't explicitly name one of the core challenges of theoretical agent-foundations work that aims to solve the "hard bits" of the alignment challenge, namely the seeming lack of reliable feedback loops that give you some indication that you are pushing towards something practically useful in the end instead of just a bunch of cool math that nonetheless resides alone in its separate magisterium. As Conor Leahy concisely put it:

Humans are really, really bad at doing long chains of abstract reasoning without regular contact with reality, so in practice imo good philosophy has to have feedback loops with reality, otherwise you will get confused.

He was talking about philosophy in particular at that juncture, in response to Wei Dai's concerns over metaphilosophical competence, but this point seems to me to generalize to a whole bunch of other areas as well. Indeed, I have talked about this before.

... and in my experience, there are people who can get traction on the core hard problems. Most notably physicists - when they grok the hard parts, they tend to immediately see footholds, rather than a blank impassable wall.

Do they get traction on "core hard problems" because of how Inherently Awesome they are as researchers, or do they do so because the types of physics problems we mostly care about currently are such that, while the generation of (worthwhile) grand mathematical theories is hard, verifying them is (comparatively) easier because we can run a bunch of experiments (or observe astronomical data etc., in the super-macro scale) to see if the answers they spit out comply with reality? I am aware of your general perspective on this matter, but I just... still completely disagree, for reasons other people have pointed out (see also Vanessa Kosoy's comment here). Is this also supposed to be an implicitly assumed bit of background material?

And when we don't have those verifying experiments at hand, do we not get stuff like string theory, where the math is beautiful and exquisite (in the domains it has been extended do) but debate by "physics postdocs" over whether it's worthwhile to keep funding and pursuing it keeps raging on as a Theory of Everything keeps eliding our grasp? I'm sure people with more object-level expertise on this can correct my potential misconceptions if need be.

Idk man, some days I'm half-tempted to believe that all non-prosaic alignment work is a bunch of "streetlighting." Yeah, it doesn't result in the kind of flashy papers full of concrete examples about current models that typically get associated with the term-in-scare-quotes. But it sure seems to cover itself in a veneer of respectability by giving a (to me) entirely unjustified appearance of rigor and mathematical precision and robustness to claims about what will happen in the real world based on nothing more than a bunch of vibing about toy models that assume away the burdensome real-world details serving as evidence whether the approaches are even on the right track. A bunch of models that seem both woefully underpowered for the Wicked Problems they must solve and also destined to underfit their target, for they (currently) all exist and supposedly apply independently of the particular architecture, algorithms, training data, scaffolding etc., that will result in the first patch of really powerful AIs. The contents and success stories of Vanessa Kosoy's desiderata, or of your own search for natural abstractions, or of Alex Altair's essence of agent foundations, or of Orthogonal's QACI, etc., seem entirely insensitive to the fact that we are currently dealing with multimodal LLMs combined with RL instead of some other paradigm, which in my mind almost surely disqualifies them as useful-in-the-real-world when the endgame hits.

There's a famous Eliezer quote about how for every correct answer to a precisely-stated problem, there are a million times more wrong answers one could have given instead. I would build on that to say that for every powerfully predictive, but lossy and reductive mathematical model of a complex real-world system, there are a million times more similar-looking mathematical models that fail to capture the essence of the problem and ultimately don't generalize well at all. And it's only by grounding yourself to reality and hugging the query tight by engaging with real-world empirics that you can figure out if the approach you've chosen is in the former category as opposed to the latter.

(I'm briefly noting that I don't fully endorse everything I said in the previous 2 paragraphs, and I realize that my framing is at least a bit confrontational and unfair. Separately, I acknowledge the existence of arguably-non-prosaic and mostly theoretical alignment approaches like davidad's Open Agency Architecture, CHAI's CIRL and utility uncertainty, Steve Byrnes's work on brain-like AGI safety, etc., that don't necessarily appear to fit this mold. I have varying opinions on the usefulness and viability of such approaches.)

I want to echo Jonas's statement and say that this was an enjoyable and thought-provoking comment to read. I appreciate the deep engagement with the questions I posed and the work that went into everything you wrote. Strong-upvoted!

I will not write a point-by-point response right now, but perhaps I will sometime soon, depending on when I get some free time. We could maybe do a dialogue about this at some point too, if you're willing, but I'm not sure when I would be up for that just yet.

Ah, gotcha. Yes, that seems reasonable.

I don't really understand why this is at all important. Do you expect (or endorse) users to... vote on posts solely by reading a list of titles without clicking on them to refresh their memories of what the posts are about, and as a natural corollary of this, see who the authors of the posts are? What's the purpose of introducing inconveniences and hiding information when this information will very likely be found anyway?

I get the importance of marginalist thinking, and of pondering what incentives you are creating for the median and/or marginal voting participant, blah blah blah, but if there is ever a spot on the Internet where superficiality is at its lowest and the focus is on the essence above the form, the LW review process might well be it. 

In light of that, this question just doesn't seem (to a rather outside observer like me) worth pondering all that much.

The 3 most important paragraphs, extracted to save readers the trouble of clicking on a link:

The Anduril and OpenAI strategic partnership will focus on improving the nation’s counter-unmanned aircraft systems (CUAS) and their ability to detect, assess and respond to potentially lethal aerial threats in real-time.

[...]

The accelerating race between the United States and China to lead the world in advancing AI makes this a pivotal moment. If the United States cedes ground, we risk losing the technological edge that has underpinned our national security for decades.

[...]

These models, which will be trained on Anduril’s industry-leading library of data on CUAS threats and operations, will help protect U.S. and allied military personnel and ensure mission success.

I appreciate your response, and I understand that you are not arguing in favor of this perspective. Nevertheless, since you have posited it, I have decided to respond to it myself and expand upon why I ultimately disagree with it (or at the very least, why I remain uncomfortable with it because it doesn't seem to resolve my confusions).

I think revealed preferences show I am a huge fan of explanations of confusing questions that ultimately claim the concepts we are reifying are ultimately inconsistent/incoherent, and that instead of hitting our heads against the wall over and over, we should take a step back and ponder the topic at a more fundamental level first. So I am certainly open to the idea that “do I nonetheless continue living (in the sense of, say, anticipating the same kind of experiences)?” is a confused question.

But, as I see it, there are a ton of problems with applying this general approach in this particular case. First of all, if anticipated experiences are an ultimately incoherent concept that we cannot analyze without first (unjustifiably) reifying a theory-ladden framework, how precisely are we to proceed from an epistemological perspective? When the foundation of 'truth' (or at least, what I conceive of it to be) is based around comparing and contrasting what we expect to see with what we actually observe experimentally, doesn't the entire edifice collapse once the essential constituent piece of 'experiences' breaks down? Recall the classic (and eternally underappreciated) paragraph from Eliezer:

I pause. “Well . . .” I say slowly. “Frankly, I’m not entirely sure myself where this ‘reality’ business comes from. I can’t create my own reality in the lab, so I must not understand it yet. But occasionally I believe strongly that something is going to happen, and then something else happens instead. I need a name for whatever-it-is that determines my experimental results, so I call it ‘reality’. This ‘reality’ is somehow separate from even my very best hypotheses. Even when I have a simple hypothesis, strongly supported by all the evidence I know, sometimes I’m still surprised. So I need different names for the thingies that determine my predictions and the thingy that determines my experimental results. I call the former thingies ‘belief,’ and the latter thingy ‘reality.’ ”

What exactly do we do once we give up on precisely pinpointing the phrases "I believe", "my [...] hypotheses", "surprised", "my predictions", etc.? Nihilism, attractive as it may be to some from a philosophical or 'contrarian coolness' perspective, is not decision-theoretically useful when you have problems to deal with and tasks to accomplish. Note that while Eliezer himself is not what he considers a logical positivist, I think I... might be?

I really don't understand what "best explanation", "true", or "exist" mean, as stand-alone words divorced from predictions about observations we might ultimately make about them.

This isn't just a semantic point, I think. If there are no observations we can make that ultimately reflect whether something exists in this (seems to me to be) free-floating sense, I don't understand what it can mean to have evidence for or against such a proposition. So I don't understand how I am even supposed to ever justifiably change my mind on this topic, even if I were to accept it as something worth discussing on the object-level.

Everything I believe, my whole theory of epistemology and everything else logically downstream of it (aka, virtually everything I believe), relies on the thesis (axiom, if you will) that there is a 'me' out there doing some sort of 'prediction + observation + updating' in response to stimuli from the outside world. I get that this might be like reifying ghosts in a Wentworthian sense when you drill down on it, but I still have desires about the world, dammit, even if they don't make coherent sense as concepts! And I want them to be fulfilled regardless.

And, moreover, one of those preferences is maintaining a coherent flow of existence, avoiding changes that would be tantamount to death (even if they are not as literal as 'someone blows my brains out'). As a human being, I have preferences over what I experience too, not just over what state the random excitations of quantum fields in the Universe are at some point past my expiration date. As far as I see, the hard problem of consciousness (i.e., the nature of qualia) has not been close to solved; any answer to it would have to give me a practical handbook for answering the initial questions I posed to jbash.

Edit: This comment misinterpreted the intended meaning of the post.

Practical CF, more explicitly: A simulation of a human brain on a classical computer, capturing the dynamics of the brain on some coarse-grained level of abstraction, that can run on a computer small and light enough to fit on the surface of Earth, with the simulation running at the same speed as base reality, would cause the same conscious experience as that brain, in the specific sense of thinking literally the exact same sequence of thoughts in the exact same order, in perpetuity.

I... don't think this is necessarily what @EuanMcLean meant? At the risk of conflating his own perspective and ambivalence on this issue with my own, this is a question of personal identity and whether the computationalist perspective, generally considered a "reasonable enough" assumption to almost never be argued for explicitly on LW, is correct. As I wrote a while ago on Rob's post:

As TAG has written a number of times, the computationalist thesis seems not to have been convincingly (or even concretely) argued for in any LessWrong post or sequence (including Eliezer's Sequences). What has been argued for, over and over again, is physicalism, and then more and more rejections of dualist conceptions of souls. 

That's perfectly fine, but "souls don't exist and thus consciousness and identity must function on top of a physical substrate" is very different from "the identity of a being is given by the abstract classical computation performed by a particular (and reified) subset of the brain's electronic circuit," and the latter has never been given compelling explanations or evidence. This is despite the fact that the particular conclusions that have become part of the ethos of LW about stuff like brain emulation, cryonics etc are necessarily reliant on the latter, not the former. 

As a general matter, accepting physicalism as correct would naturally lead one to the conclusion that what runs on top of the physical substrate works on the basis of... what is physically there (which, to the best of our current understanding, can be represented through Quantum Mechanical probability amplitudes), not what conclusions you draw from a mathematical model that abstracts away quantum randomness in favor of a classical picture, the entire brain structure in favor of (a slightly augmented version of) its connectome, and the entire chemical make-up of it in favor of its electrical connections. As I have mentioned, that is a mere model that represents a very lossy compression of what is going on; it is not the same as the real thing, and conflating the two is an error that has been going on here for far too long. Of course, it very well might be the case that Rob and the computationalists are right about these issues, but the explanation up to now should make it clear why it is on them to provide evidence for their conclusion.

I recognize you wrote in response to me a while ago that you "find these kinds of conversations to be very time-consuming and often not go anywhere." I understand this, and I sympathize to a large extent: I also find these discussions very tiresome, which became part of why I ultimately did not engage too much with some of the thought-provoking responses to the question I posed a few months back. So it's totally ok for us not to get into the weeds of this now (or at any point, really). Nevertheless, for the sake of it, I think the "everyday experience" thermostat example does not seem like an argument in favor of computationalism over physicalism-without-computationalism, since the primary generator of my intuition that my identity would be the same in that case is the literal physical continuity of my body throughout that process. I just don't think there is a "prosaic" (i.e., bodily-continuity-preserving) analogue or intuition pump to the case of WBE or similar stuff in this respect.

Anyway, in light of footnote 10 in the post ("The question of whether such a simulation contains consciousness at all, of any kind, is a broader discussion that pertains to a weaker version of CF that I will address later on in this sequence"), which to me draws an important distinction between a brain-simulation having some consciousness/identity versus having the same consciousness/identity as that of whatever (physically-instantiated) brain it draws from, I did want to say that this particular post seems focused on the latter and not the former, which seems quite decision-relevant to me:

jbash: These various ideas about identity don't seem to me to be things you can "prove" or "argue for". They're mostly just definitions that you adopt or don't adopt. Arguing about them is kind of pointless.

sunwillrise: I absolutely disagree. The basic question of "if I die but my brain gets scanned beforehand and emulated, do I nonetheless continue living (in the sense of, say, anticipating the same kinds of experiences)?" seems the complete opposite of pointless, and the kind of conundrum in which agreeing or disagreeing with computationalism leads to completely different answers.

Perhaps there is a meaningful linguistic/semantic component to this, but in the example above, it seems understanding the nature of identity is decision-theoretically relevant for how one should think about whether WBE would be good or bad (in this particular respect, at least).

All of these ideas sound awesome and exciting, and precisely the right kind of use of LLMs that I would like to see on LW!