The part where squiggles are small and simple is unimportant. They could be bigger and more complicated, like building giant mechanical clocks. The part that matters is that squiggles/paperclips are of no value even from a very cosmopolitan and embracing perspective on value.
Eliezer Yudkowsky
Karma: 142,677
Universal Basic Income and Poverty
I think that the AI’s internal ontology is liable to have some noticeable alignments to human ontology w/r/t the purely predictive aspects of the natural world; it wouldn’t surprise me to find distinct thoughts in there about electrons. As the internal ontology goes to be more about affordances and actions, I expect to find increasing disalignment. As the internal ontology takes on any reflective aspects, parts of the representation that mix with facts about the AI’s internals, I expect to find much larger differences—not just that the AI has a different concept boundary around “easy to understand”, say, but that it maybe doesn’t have any such internal notion as “easy to understand” at all, because easiness isn’t in the environment and the AI doesn’t have any such thing as “effort”. Maybe it’s got categories around yieldingness to seven different categories of methods, and/or some general notion of “can predict at all / can’t predict at all”, but no general notion that maps onto human “easy to understand”—though “easy to understand” is plausibly general-enough that I wouldn’t be unsurprised to find a mapping after all.
Corrigibility and actual human values are both heavily reflective concepts. If you master a requisite level of the prerequisite skill of noticing when a concept definition has a step where its boundary depends on your own internals rather than pure facts about the environment—which of course most people can’t do because they project the category boundary onto the environment, but I have some credit that John Wentworth might be able to do it some—and then you start mapping out concept definitions about corrigibility or values or god help you CEV, that might help highlight where some of my concern about unnatural abstractions comes in.
Entirely separately, I have concerns about the ability of ML-based technology to robustly point the AI in any builder-intended direction whatsoever, even if there exists some not-too-large adequate mapping from that intended direction onto the AI’s internal ontology at training time. My guess is that more of the disagreement lies here.
What the main post is responding to is the argument: “We’re just training AIs to imitate human text, right, so that process can’t make them get any smarter than the text they’re imitating, right? So AIs shouldn’t learn abilities that humans don’t have; because why would you need those abilities to learn to imitate humans?” And to this the main post says, “Nope.”
The main post is not arguing: “If you abstract away the tasks humans evolved to solve, from human levels of performance at those tasks, the tasks AIs are being trained to solve are harder than those tasks in principle even if they were being solved perfectly.” I agree this is just false, and did not think my post said otherwise.
Unless I’m greatly misremembering, you did pick out what you said was your strongest item from Lethalities, separately from this, and I responded to it. You’d just straightforwardly misunderstood my argument in that case, so it wasn’t a long response, but I responded. Asking for a second try is one thing, but I don’t think it’s cool to act like you never picked out any one item or I never responded to it.
EDIT: I’m misremembering, it was Quintin’s strongest point about the Bankless podcast. https://www.lesswrong.com/posts/wAczufCpMdaamF9fy/my-objections-to-we-re-all-gonna-die-with-eliezer-yudkowsky?commentId=cr54ivfjndn6dxraD
If Quintin hasn’t yelled “Empiricism!” then it’s not about him. This is more about (some) e/accs.
‘Empiricism!’ as Anti-Epistemology
Wow, that’s fucked up.
I am denying that superintelligences play this game in a way that looks like “Pick an ordinal to be your level of sophistication, and whoever picks the higher ordinal gets $9.” I expect sufficiently smart agents to play this game in a way that doesn’t incentivize attempts by the opponent to be more sophisticated than you, nor will you find yourself incentivized to try to exploit an opponent by being more sophisticated than them, provided that both parties have the minimum level of sophistication to be that smart.
If faced with an opponent stupid enough to play the ordinal game, of course, you just refuse all offers less than $9, and they find that there’s no ordinal level of sophistication they can pick which makes you behave otherwise. Sucks to be them!
You have misunderstood (1) the point this post was trying to communicate and (2) the structure of the larger argument where that point appears, as follows:
First, let’s talk about (2), the larger argument that this post’s point was supposed to be relevant to.
Is the larger argument that superintelligences will misunderstand what we really meant, due to a lack of knowledge about humans?
It is incredibly unlikely that Eliezer Yudkowsky in particular would have constructed an argument like this, whether in 2007, 2017, or even 1997. At all of these points in my life, I visibly held quite a lot of respect for the epistemic prowess of superintelligences. They were always going to know everything relevant about the complexities of human preference and desire. The larger argument is about whether it’s easy to make superintelligences end up caring.
This post isn’t about the distinction between knowing and caring, to be clear; that’s something I tried to cover elsewhere. The relevant central divide falls in roughly the same conceptual place as Hume’s Guillotine between ‘is’ and ‘ought’, or the difference between the belief function and the utility function.
(I don’t see myself as having managed to reliably communicate this concept (though the central idea is old indeed within philosophy) to the field that now sometimes calls itself “AI alignment”; so if you understand this distinction yourself, you should not assume that any particulary commentary within “AI alignment” is written from a place of understanding it too.)
What this post is about is the amount of information-theoretic complexity that you need to get into the system’s preferences, in order to have that system, given unlimited or rather extremely large amounts of power, deliver to you what you want.
It doesn’t argue that superintelligences will not know this information. You’ll note that the central technology in the parable isn’t an AI; it’s an Outcome Pump.
What it says, rather, is that there might be, say, a few tens of thousands of bits—the exact number is not easy to estimate, we just need to know that it’s more than a hundred bits and less than a billion bits and anything in that range is approximately the same problem from our standpoint—that you need to get into the steering function. If you understand the Central Divide that Hume’s Razor points to, the distinction between probability and preference, etcetera, the post is trying to establish the idea that we need to get 13,333 bits or whatever into the second side of this divide.
In terms of where this point falls within the larger argument, this post is not saying that it’s particularly difficult to get those 13,333 bits into the preference function; for all this post tries to say, locally, maybe that’s as easy as having humans manually enter 13,333 yes-or-no answers into the system. It’s not talking about the difficulty of doing the work but rather the amount and nature of a kind of work that needs to be done somehow.
Definitely, the post does not say that it’s hard to get those 13,333 bits into the belief function or knowledge of a superintelligence.
Separately from understanding correctly what this post is trying to communicate, at all, in 2007, there’s the question of whether modern LLMs have anything to say about—obviously not the post’s original point—but rather, other steps of the larger question in which this post’s point appears.
Modern LLMs, if you present them with a text-based story like the one in this parable, are able to answer at least some text-based questions about whether you’d prefer your grandmother to be outside the building or be safely outside the building. Let’s admit this premised observation at face value. Have we learned thereby the conclusion that it’s easy to get all of that information into a superintelligence’s preference function?
And if we say “No”, is this Eliezer making up post-hoc excuses?
What exactly we learn from the evidence of how AI has played out in 2024 so far, is the sort of thing that deserves its own post. But I observe that if you’d asked Eliezer-2007 whether an (Earth-originating) superintelligence could correctly predict the human response pattern about what to do with the grandmother—solve the same task LLMs are solving, to at least the LLM’s performance level—Eliezer-2007 would have unhesitatingly answered “yes” and indeed “OBVIOUSLY yes”.
How is this coherent? Because the post’s point is about how much information needs to get into the preference function. To predict a human response pattern you need (only) epistemic knowledge. This is part of why the post is about needing to give specifications to an Outcome Pump, rather than it depicting an AI being surprised by its continually incorrect predictions about a human response pattern.
If you don’t see any important distinction between the two, then of course you’ll think that it’s incoherent to talk about that distinction. But even if you think that Hume was mistaken about there existing any sort of interesting gap between ‘is’ and ‘ought’, you might by some act of empathy be able to imagine that other people think there’s an interesting subject matter there, and they are trying to talk about it with you; otherwise you will just flatly misunderstand what they were trying to say, and mispredict their future utterances. There’s a difference between disagreeing with a point, and just flatly failing to get it, and hopefully you aspire to the first state of mind rather than the second.
Have we learned anything stunningly hopeful from modern pre-AGIs getting down part of the epistemic part of the problem at their current ability levels, to the kind of resolution that this post talked about in 2007? Or from it being possible to cajole pre-AGIs with loss functions into willingly using that knowledge to predict human text outputs? Some people think that this teaches us that alignment is hugely easy. I think they are mistaken, but that would take its own post to talk about.
But people who point to “The Hidden Complexity of Wishes” and say of it that it shows that I had a view which the current evidence already falsifies—that I predicted that no AGI would ever be able to predict human response patterns about getting grandmothers out of burning buildings—have simply: misunderstood what the post is about, not understood in particular why the post is about an Outcome Pump rather than an AI stupidly mispredicting human responses, and failed to pick up on the central point that Eliezer expects superintelligences to be smart in the sense of making excellent purely epistemic predictions.
This deserves a longer answer than I have time to allocate it, but I quickly remark that I don’t recognize the philosophy or paradigm of updatelessness as refusing to learn things or being terrified of information; a rational agent should never end up in that circumstance, unless some perverse other agent is specifically punishing them for having learned the information (and will lose of their own value thereby; it shouldn’t be possible for them to gain value by behaving “perversely” in that way, for then of course it’s not “perverse”). Updatelessness is, indeed, exactly that sort of thinking which prevents you from being harmed by information, because your updateless exposure to information doesn’t cause you to lose coordination with your counterfactual other selves or exhibit dynamic inconsistency with your past self.
From an updateless standpoint, “learning” is just the process of reacting to new information the way your past self would want you to do in that branch of possibility-space; you should never need to remain ignorant of anything. Maybe that involves not doing the thing that would then be optimal when considering only the branch of reality you turned out to be inside, but the updateless mind denies that this was ever the principle of rational choice, and so feels no need to stay ignorant in order to maintain dynamic consistency.
They can solve it however they like, once they’re past the point of expecting things to work that sometimes don’t work. I have guesses but any group that still needs my hints should wait and augment harder.
I disagree with my characterization as thinking problems can be solved on paper, and with the name “Poet”. I think the problems can’t be solved by twiddling systems weak enough to be passively safe, and hoping their behavior generalizes up to dangerous levels. I don’t think paper solutions will work either, and humanity needs to back off and augment intelligence before proceeding. I do not take the position that we need a global shutdown of this research field because I think that guessing stuff without trying it is easy, but because guessing it even with some safe weak lesser tries is still impossibly hard. My message to humanity is “back off and augment” not “back off and solve it with a clever theory”.
Not what comes up for me, when I go incognito and google AI risk lesswrong.
I rather expect that existing robotic machinery could be controlled by ASI rather than “moderately smart intelligence” into picking up the pieces of a world economy after it collapses, or that if for some weird reason it was trying to play around with static-cling spaghetti It could pick up the pieces of the economy that way too.
It’s false that currently existing robotic machinery controlled by moderately smart intelligence can pick up the pieces of a world economy after it collapses. One well-directed algae cell could, but not existing robots controlled by moderate intelligence.
What does this operationalize as? Presumably not that if we load a bone and a diamond rod under equal pressures, the diamond rod breaks first? Is it more about if we drop sudden sharp weights onto a bone rod and a diamond rod, the diamond rod breaks first? I admit I hadn’t expected that, despite a general notion that diamond is crystal and crystals are unexpectedly fragile against particular kinds of hits, and if so that modifies my sense of what’s a valid metaphor to use.
“Pandemics” aren’t a locally valid substitute step in my own larger argument, because an ASI needs its own manufacturing infrastructure before it makes sense for the ASI to kill the humans currently keeping its computers turned on. So things that kill a bunch of humans are not a valid substitute for being able to, eg, take over and repurpose the existing solar-powered micron-diameter self-replicating factory systems, aka algae, and those repurposed algae being able to build enough computing substrate to go on running the ASI after the humans die.
It’s possible this argument can and should be carried without talking about the level above biology, but I’m nervous that this causes people to start thinking in terms of Hollywood movie plots about defeating pandemics and hunting down the AI’s hidden cave of shoggoths, rather than hearing, “And this is a lower bound but actually in real life you just fall over dead.”
Why is flesh weaker than diamond? Diamond is made of carbon-carbon bonds. Proteins also have some carbon-carbon bonds! So why should a diamond blade be able to cut skin?
I reply: Because the strength of the material is determined by its weakest link, not its strongest link. A structure of steel beams held together at the vertices by Scotch tape (and lacking other clever arrangements of mechanical advantage) has the strength of Scotch tape rather than the strength of steel.
Or: Even when the load-bearing forces holding large molecular systems together are locally covalent bonds, as in lignin (what makes wood strong), if you’ve got larger molecules only held together by covalent bonds at interspersed points along their edges, that’s like having 10cm-diameter steel beams held together by 1cm welds. Again, barring other clever arrangements of mechanical advantage, that structure has the strength of 1cm of steel rather than 10cm of steel.
Bone is stronger than wood; it runs on a relatively stronger structure of ionic bonds, which are no locally weaker than carbon bonds in terms of attojoules of potential energy per bond. Bone is weaker than diamond, then, because… why?
Well, partially, IIUC, because calcium atoms are heavier than carbon atoms. So even if per-bond the ionic forces are strong, some of that is lost in the price you pay for including heavier atoms whose nuclei have more protons that are able to exert the stronger electrical forces making up that stronger bond.
But mainly, bone is so much weaker than diamond (on my understanding) because the carbon bonds in diamond have a regular crystal structure that locks the carbon atoms into relative angles, and in a solid diamond this crystal structure is tesselated globally. Hydroxyapatite (the crystal part of bone) also tesselates in an energetically favorable configuration; but (I could be wrong about this) it doesn’t have the same local resistance to local deformation; and also, the actual hydroxyapatite crystal is assembled by other tissues that layer the ionic components into place, which means that a larger structure of bone is full of fault lines. Bone cleaves along the weaker fault line, not at its strongest point.
But then, why don’t diamond bones exist already? Not just for the added strength; why make the organism look for calcium and phosphorus instead of just carbon?
The search process of evolutionary biology is not the search of engineering; natural selection can only access designs via pathways of incremental mutations that are locally advantageous, not intelligently designed simultaneous changes that compensate for each other. There were, last time I checked, only three known cases where evolutionary biology invented the freely rotating wheel. Two of those known cases are ATP synthase and the bacterial flagellum, which demonstrates that freely rotating wheels are in fact incredibly useful in biology, and are conserved when biology stumbles across them after a few hundred million years of search. But there’s no use for a freely rotating wheel without a bearing and there’s no use for a bearing without a freely rotating wheel, and a simultaneous dependency like that is a huge obstacle to biology, even though it’s a hardly noticeable obstacle to intelligent engineering.
The entire human body, faced with a strong impact like being gored by a rhinocerous horn, will fail at its weakest point, not its strongest point. How much evolutionary advantage is there to stronger bone, if what fails first is torn muscle? How much advantage is there to an impact-resistant kidney, if most fights that destroy a kidney will kill you anyways? Evolution is not the sort of optimizer that says, “Okay, let’s design an entire stronger body.” (Analogously, the collection of faults that add up to “old age” is large enough that a little more age resistance in one place is not much of an advantage if other aging systems or outward accidents will soon kill you anyways.)
I don’t even think we have much of a reason to believe that it’d be physically (rather than informationally) difficult to have a set of enzymes that synthesize diamond. It could just require 3 things to go right simultaneously, and so be much much harder to stumble across than tossing more hydroxyapatite to lock into place in a bone crystal. And then even if somehow evolution hit on the right set of 3 simultaneous mutations, sometime over the history of Earth, the resulting little isolated chunk of diamond probably would not be somewhere in the phenotype that had previously constituted the weakest point in a mechanical system that frequently failed. If evolution has huge difficulty inventing wheels, why expect that it could build diamond chainmail, even assuming that diamond chainmail is physically possible and could be useful to an organism that had it?
Talking to the general public is hard. The first concept I’m trying to convey to them is that there’s an underlying physical, mechanical reason that flesh is weaker than diamond; and that this reason isn’t that things animated by vitalic spirit, elan vital, can self-heal and self-reproduce at the cost of being weaker than the cold steel making up lifeless machines, as is the price of magic imposed by the universe to maintain game balance. This is a very natural way for humans to think; and the thing I am trying to come in and do is say, “Actually, no, it’s not a mystical balance, it’s that diamond is held together by bonds that are hundreds of kJ/mol; and the mechanical strength of proteins is determined by forces a hundred times as weak as that, the part where proteins fold up like spaghetti held together by static cling.”
There is then a deeper story that’s even harder to explain, about why evolution doesn’t build freely rotating wheels or diamond chainmail; why evolutionary design doesn’t find the physically possible stronger systems. But first you need to give people a mechanical intuition for why, in a very rough intuitive sense, it is physically possible to have stuff that moves and lives and self-repairs but is strong like diamond instead of flesh, without this violating a mystical balance where the price of vitalic animation is lower material strength.
And that mechanical intuition is: Deep down is a bunch of stuff that, if you could see videos of it, would look more like tiny machines than like magic, though they would not look like familiar machines (very few freely rotating wheels). Then why aren’t these machines strong like human machines of steel are strong? Because iron atoms are stronger than carbon atoms? Actually no, diamond is made of carbon and that’s still quite strong. The reason is that these tiny systems of machinery are held together (at the weakest joints, not the strongest joints!) by static cling.
And then the deeper question: Why does evolution build that way? And the deeper answer: Because everything evolution builds is arrived at as an error, a mutation, from something else that it builds. Very tight bonds fold up along very deterministic pathways. So (in the average case, not every case) the neighborhood of functionally similar designs is densely connected along shallow energy gradients and sparsely connected along deep energy gradients. Intelligence can leap long distances through that design space using coordinated changes, but evolutionary exploration usually cannot.
And I do try to explain that too. But it is legitimately more abstract and harder to understand. So I lead with the idea that proteins are held together by static cling. This is, I think, validly the first fact you lead with if the audience does not already know it, and just has no clue why anyone could possibly possibly think that there might even be machinery that does what bacterial machinery does but better. The typical audience is not starting out with the intuition that one would naively think that of course you could put together stronger molecular machinery, given the physics of stronger bonds, and then we debate whether (as I believe) the naive intuition is actually just valid and correct; they don’t understand what the naive intuition is about, and that’s the first thing to convey.
If somebody then says, “How can you be so ignorant of chemistry? Some atoms in protein are held together by covalent bonds, not by static cling! There’s even eg sulfur bonds whereby some parts of the folded-spaghetti systems end up glued together with real glue!” then this does not validly address the original point because: the underlying point about why flesh is more easily cleaved than diamond, is about the weakest points of flesh rather than the strongest points in flesh, because that’s what determines the mechanical strength of the larger system.
I think there is an important way of looking at questions like these where, at the final end, you ask yourself, “Okay, but does my argument prove that flesh is in fact as strong as diamond? Why isn’t flesh as strong as diamond, then, if I’ve refuted the original argument for why it isn’t?” and this is the question that leads you to realize that some local strong covalent bonds don’t matter to the argument if those bonds aren’t the parts that break under load.
My main moral qualm about using the Argument From Folded Spaghetti Held Together By Static Cling as an intuition pump is that the local ionic bonds in bone are legitimately as strong per-bond as the C-C bonds in diamond, and the reason that bone is weaker than diamond is (iiuc) actually more about irregularity, fault lines, and resistance to local deformation than about kJ/mol of the underlying bonds. If somebody says “Okay, fine, you’ve validly explained why flesh is weaker than diamond, but why is bone weaker than diamond?” I have to reply “Valid, iiuc that’s legit more about irregularity and fault lines and interlaced weaker superstructure and local deformation resistance of the bonds, rather than the raw potential energy deltas of the load-bearing welds.”
Actually, to slightly amend that: The part where squiggles are small is a more than randomly likely part of the prediction, but not a load-bearing part of downstream predictions or the policy argument. Most of the time we don’t needlessly build our own paperclips to be the size of skyscrapers; even when having fun, we try to do the fun without vastly more resources, than are necessary to that amount of fun, because then we’ll have needlessly used up all our resources and not get to have more fun. We buy cookies that cost a dollar instead of a hundred thousand dollars. A very wide variety of utility functions you could run over the outside universe will have optima around making lots of small things because each thing scores one point, and so to score as many points as possible, each thing is as small as it can be as still count as a thing. Nothing downstream depends on this part coming true and there are many ways for it to come false; but the part where the squiggles are small and molecular is an obvious kind of guess. “Great giant squiggles of nickel the size of a solar system would be no more valuable, even from a very embracing and cosmopolitan perspective on value” is the loadbearing part.