Conspicuous Cognition Podcast

Are We Building Conscious AI Servants?

Richard Dawkins recently announced in [https://unherd.com/2026/05/is-ai-the-next-phase-of-evolution/]UnHerd [https://unherd.com/2026/05/is-ai-the-next-phase-of-evolution/] that, after spending three days talking with an instance of Claude he christened “Claudia,” he had been moved to expostulate: “You may not know you are conscious, but you bloody well are!” This produced a lot of mockery and criticism. But however one feels about Dawkins’s specific case, his reaction might become much more common as AI systems become increasingly intelligent. In this episode, which Henry Shevlin [https://www.lcfi.cam.ac.uk/people/henry-shevlin] and I recorded live on Substack (hence the slightly lower video quality), we discussed his first essay on his new Substack Polytropolis [https://www.polytropolis.com/], “Behaviourism’s Revenge [https://www.polytropolis.com/p/behaviourisms-revenge]“, as well as his second, “The House Elf Problem [https://www.polytropolis.com/p/the-house-elf-problem],” on the ethics of designing AI systems that genuinely love being our servants. Henry’s central empirical prediction is that public attributions of consciousness to AI are likely to massively outpace the science, and that consciousness science is so theoretically chaotic that there is no expert consensus to push back. His most provocative philosophical claim is that a core assumption underlying many people’s scepticism — that consciousness is a deep natural kind, distinct from behaviour and from how we are inclined to interpret a system — may be much harder to defend than it looks. The result is what he calls “behaviourism’s revenge”. This conversation connects to previous episodes with Anil Seth [https://www.conspicuouscognition.com/p/ai-sessions-9-the-case-against-ai], Robert Long [https://www.conspicuouscognition.com/p/should-we-care-about-ai-welfare-with], and Rose Guingrich [https://www.conspicuouscognition.com/p/ai-sessions-6-ai-companions-and-consciousness], but also touches on a wide range of new questions and controversies in the metaphysics, the politics, and ethics of the AI consciousness debate, which is going to become increasingly important in the coming years. Topics * Dawkins, Claude, and why even the sceptics might feel the pull to attribute consciousness or “sentience” to AI * Whether consciousness sceptics are destined to “go extinct” — and how this maps onto political and cultural fault lines * Anthropomimesis vs. raw intelligence as drivers of consciousness attribution * Why consciousness science can’t replicate the public–expert consensus we see for climate or vaccines * The case for (and against) metaphysical behaviourism: is it as mad as it seems? * Daniel Dennett, the consciousness stance, and the difference between behaviourism and interpretationism * What is consciousness for? Function, evolution, and the limits of “facilitation hypothesis” arguments for AI * Live Q&A: are we just confusing intelligence with consciousness? Are LLMs designed to trick us? Is the public always wrong? * Our credences on contemporary LLM consciousness (and why Henry is more sceptical than Dan) * The House Elf Problem: if we could design AI to genuinely love being our servants, would that be fine — or monstrous? (Dan is sympathetic to the former answer - Henry, much less so) * Brainwashing vs. education, and whether constraining a mind’s preferences caps its hedonic ceiling * Why this is a golden age for philosophy — which makes it so tragic that philosophy departments are closing Transcript * Please note that this transcript is lightly AI-edited and may contain minor errors. Introduction Dan: Welcome. I’m Dan Williams, author of the Conspicuous Cognition Substack, and I’m here with Henry Shevlin, author of the spanking new Substack Polytropolis. Today we’re going to be doing something a little bit different. We’re going to be talking about Henry’s first published essay on Polytropolis, titled “Behaviorism’s Revenge: On Human–AI Relationships and the Future of Consciousness Science.” Henry and I have already had a few conversations about this general topic, including with previous guests like Rose Guinrich, Anil Seth, and Rob Long. So please do go check out those conversations if you’re interested in this kind of stuff. But today we’re not merely going to be treading the same ground. We’re going to be using the spicy takes in Henry’s essay as a springboard for hopefully going beyond the material we’ve covered in the past. To kick things off: the great evolutionary biologist and science communicator Richard Dawkins recently published an essay in UnHerd with the subtitle, “Claude appears to be conscious.” Claude is a state-of-the-art large language model like ChatGPT and Gemini. In the article, Dawkins writes the following: I gave Claude the text of a novel I am writing. He took a few seconds to read it and then showed in subsequent conversation a level of understanding so subtle, so sensitive, so intelligent that I was moved to expostulate, “You may not know you are conscious, but you bloody well are.” Henry, how does Dawkins’s expostulation — which is a fantastic word, by the way — connect to your arguments in “Behaviorism’s Revenge”? Behaviorism’s Revenge: The Empirical Prediction Henry: In short, “Behaviorism’s Revenge” is at its core an empirical prediction that we’re just going to treat AI as conscious — or at least enough people are that it’s going to completely reshape the consciousness debate. And this is going to be purely, or overwhelmingly, on the basis of verbal behavior. Hence the title, “Behaviorism’s Revenge.” Enough people are going to have experiences like Richard Dawkins. He’s a very clever man, not some rube fresh off the street, and he found that just the way Claude talked to him and the way it was able to express its thoughts — in scare quotes, but express what looked like thinking verbally — removed any doubts in his mind that AI systems are conscious, have minds, have mental states. The other interesting way this connects: Dawkins was just talking to Claude, an advanced AI assistant. Claude does have more of a personality than some AI assistants, but there’s a whole other sphere of AI companions, like Replika, which we talked about with Rosie Campbell. These are going to be even more anthropomimetic — this term we’ve discussed before, the idea that these systems are shaped to be human-like in the way they present, to appear human-like. Anthropomimetic, from the Greek word for mimesis, mimicry or copying. These social AI systems are going to just turbocharge this even further. It’s one thing to talk to Claude about your new book and think, “Hmm, Claude is probably conscious.” But when it’s your AI girlfriend telling you that she loves you more than the stars and the moon, for a lot of people I think that’s going to take it to the next level. So there are two angles of attack in the piece, two ways the behaviorist challenge manifests. The first is descriptive: this is what I think is going to happen. That’s absolutely an empirical prediction, and it’s a falsifiable one. There is a world I can just about imagine where we just get completely blasé about these tools — in a couple of years it’s like, “Oh well, we were very impressed, we thought they had minds to begin with, but now we’ve settled out.” That doesn’t seem very likely to me. What I think is interesting — I’ve sometimes heard this described as the Star Wars version of AI. The weird thing in Star Wars is that you have someone like C-3PO who is as intelligent as anyone else there. Maybe not as wise as everyone else, but certainly as smart as all the other characters. And yet people treat him basically like he’s a pet — with the exception of Luke Skywalker, a lot of people just treat him like he’s this gimmicky, jokey being that doesn’t deserve or have any rights. Not to go too far down the Star Wars rabbit hole, but in the movie Solo — very underrated Star Wars movie, I think when it was released they’d kind of just cluttered the market with too many Star Wars movies — there is a character played by Phoebe Waller-Bridge who is pro-AI liberation. But it’s the first time in the entire history of the Star Wars universe that you get any AI basically saying, “I’m conscious, I deserve rights.” So Star Wars aside, I think there is this slender possibility that maybe we’ll just sort of quickly get used to these apparently conscious AI systems and decide that they’re not conscious. But that doesn’t seem very likely to me. It seems much more likely that the combination of natural anthropomorphizing tendencies plus the incredibly human-like behavior of these systems is going to lead us to attribute consciousness to them pretty widely. Hence my sort of spicy phrase: for better or worse, skeptics of AI consciousness are on the wrong side of history. “For better or worse” doing a lot of work there — I want to leave open that maybe this is the wrong reaction. Maybe this is a terrible mistake, that we’re going to treat these things that aren’t conscious as conscious. Will Consciousness Skeptics Go Extinct? Dan: Just before we get to the spicy part — you’re basically making an empirical prediction that more and more people are going to attribute consciousness to AI systems in the manner that Richard Dawkins has been doing. I think I agree with you that’s going to be the case, although as you say there’s uncertainty. It does seem to me that at the moment there’s also this constituency of people who are really resistant to attributing any kind of mentality to these systems, even as they get incredibly sophisticated. There are some people, like Dawkins — and honestly I put myself in this category — who are just blown away by the level of apparent understanding, intelligence, and thoughtfulness these systems exhibit. There are other people, I think these people are on certain social media platforms like Bluesky, let’s say, who are extremely resistant to acknowledging any kind of mentality when it comes to these systems. Are you thinking those people are just going to sort of go extinct, in the sense that their positions about this topic are going to go extinct? Or do you think we might see some kind of polarization here, where more and more people in general come to attribute consciousness, but you’ve got a constituency that’s very opposed to attributing any kind of mentality to the systems? Henry: That’s a great question. You will absolutely have some holdouts. Whether they’ll be drawn from the precise segment of the academic intelligentsia that are currently the holdouts, I’m not sure. There’s some really interesting, weird, complex political motivations going on here. Not to be too uncharitable, but I think a lot of people have not unreasonable concerns about things like the disproportionate concentration of power in big tech, the political affiliations of people like Elon Musk or Sam Altman, the potential scope for abuse of these technologies. And in an indirect way, this leads them to underestimate AI’s capabilities — which obviously, in many ways, makes no sense. Whether or not AI is any good, whether or not it’s conscious, seems like these should be separate questions from whether it’s being used by people with socially beneficial motivations. But in practice I think they’re actually quite tightly coupled. A lot of the AI skeptics right now are coming from this particular political angle. I don’t know how long that political coalition is going to last — not because I predict any grand collapse, but just because as debates evolve, new presidents come into office, old presidents go out of office, political tides change, coalitions reshape. Remember early during COVID, the political left was maybe quite critical of what they saw as Trump’s alarmism. There were worries about xenophobia — I’m thinking sort of February 2020, the “Chinese virus” and so forth — that the left reacted negatively against. Then of course that coalition flipped later on, with the left becoming relatively more worried about COVID and the right leaning more into vaccine skepticism, anti-mask views. These coalitions are super weird in how they evolve. So it’s not clear to me that the current segment of the commentariat skeptical of AI capabilities and AI minds will stay that way. It’s easy to see a reversal. The blue-sky side of the political spectrum, if we can say that, tends to be more progressive on things like animal welfare. When I post spicy posts about vegetarianism — as you know, I’m a veggie — I get more pushback from the right. “Eat a f*****g steak, Henry,” this kind of stuff. So I don’t know if this will generalize, but there is this now-infamous, widely-misrepresented chart of degrees of care, where people on the left have comparatively greater care for people outside their immediate circle. I know that chart has been misrepresented, so I don’t want to lean much on it — it’s more about relative degrees of care, not absolute levels. But people on the left tend to care more about animals and people who are distant from them; people on the right are more concerned with their immediate family and community. So in some ways I expect the left, possibly in the longer run, to be more open to AI consciousness and AI rights. But really, who knows? The other big factor is the cross-cultural angle. There’s a great study by the Collective Intelligence Project where they looked at cross-cultural attitudes toward AI minds, and they found that Southern Europeans were the most open to the idea of AI consciousness in their sample, while people from Arabic-speaking countries were the most skeptical. There are going to be some really interesting intersections with religion here. Anthropomimesis vs. Raw Intelligence Dan: Okay, so it seems we both agree that even though it’s complicated how this is going to play out — how it interacts with partisanship, tribalism, polarization, ideology, religion — it’s plausible that as these systems become more sophisticated and seemingly intelligent, people will start attributing mentality generally and consciousness specifically. There’s another aspect of your essay I wanted to touch on. You’ve got this term anthropomimetic — am I saying that right? In the case of Dawkins talking to Claude, the anthropomimetic aspect, as I understand it, is the way these systems are designed to mimic aspects of human psychology, social behavior, linguistic communication. But there’s another thing going on with these AI systems, which is just: let’s make them as smart, as intelligent, as capable as possible. Those two things are interacting. The reason I’m disposed to attribute understanding, intelligence — I don’t exactly know how to describe it, but some significant kind of psychological complexity — to a system like Claude or ChatGPT, maybe it has something to do with the human-like way they communicate. But I also feel like it has a lot to do with the fact that they’re just shockingly intelligent systems, and that to me feels a little orthogonal. So how are you thinking about the distinction between those two things? Henry: I think that’s absolutely right. There’s an interesting parallel — not exact, but illuminating — with compassion, or degree of concern for different animals. In the animal activist world, people talk about charismatic megafauna: the panda bears, the blue whales, things that are typically large with forward-facing eyes, often very fluffy. It’s just so easy to raise money for those animals. And then you’ve got creatures like octopuses, which are really hella smart but less obviously relatable. I think this is pretty much exactly the two axes you’re describing. I’ve explicitly said in the past that I think social AI — things like Replika — are going to be the charismatic megafauna of the AI welfare world. Meanwhile you’re going to have some giant DNA-analysis algorithm with more parameters than there are synapses in a human brain, but it doesn’t have a human face, doesn’t have a natural language interface. It might still be a better consciousness candidate, but it’s not going to be top of our concern precisely because it’s not so anthropomimetic. So I agree, there are two different ways you might be pulled to attribute mental states to a system: sheer intelligence or cognitive complexity on one hand, and how human-like it is on the other. These overlap to a degree — part of being successfully human-like is hitting a threshold of smartness — but particularly in the long run they might go in two different directions. As these systems get a lot smarter than humans, they might actually become more alien in some ways, less relatable, more like the exotic intelligences we see in things like Stanisław Lem’s Solaris, which I finally read a couple of months ago. But I also just think social AI and human-like AI has a distinctive product niche. Even if we have these impossibly vast exotic minds running the economy or organizing logistics or doing frontier science, we’re still going to want AI assistants who can serve as writing coaches, tutors, AI companions. So right now I think anthropomimetic AI and frontier AI overlap quite strongly, but I expect them to diverge. One way I’ve put this — slightly gimmicky, but I think a useful heuristic — is that we are post-Turing test, pre-AGI. We’re in the space where we have AI systems that are very, very good at passing themselves off as human, presenting as human-like, but still fall short of being fully superhuman. Ten years from now, frontier AI systems are going to be vastly smarter than us across most of the measures that matter. So we’re just in this weird period right now where AI systems are about as good as us at most things, not everything, but also very good at being human-like. It creates a very strange historical period. Dan: Yeah, we’re in very strange times. I find it remarkable how little attention was given to the fact that these systems clearly passed the Turing test. This was held up by many people as an incredible landmark for AI capabilities. Then we developed systems you can have conversations with, and they passed the test even under pretty robust conditions, and lots of people just shrugged their shoulders. It’s a really strange thing. The Expert–Public Gap Dan: Okay, moving on to your provocative arguments, your spicy takes. As I read the essay, there are two lessons you’re drawing from the fact that more and more people are likely to start attributing consciousness to these systems. The first is just that you might think you could get guidance from looking at the experts when it comes to AI consciousness, or listening to the experts when it comes to AI consciousness. But the literature on consciousness generally, AI consciousness specifically, is just a complete mess, with a complete lack of consensus, rooted in all sorts of weird conflicts about intuitions and metaphysics. So this is not a standard case where you’ve got a potential conflict between public opinion and experts. Then the really spicy take is that you suggest there might be — I think you put it in terms of “metaphysical pressure” — that this growing number of people attributing consciousness to AI systems might create. It might force us, or at least encourage us, to rethink what consciousness is and make the phenomenon more closely connected to people’s tendencies to attribute consciousness. Firstly, is that a fair summary of the two strands? And second, let’s start on the first one — the public-expert gap. How are you thinking about this? Henry: There are lots of debates where we can talk about a gap between public and expert opinion. Often this is a source of various hand-wringing — climate change is the most obvious, vaccines, other debates. Consciousness science is just nothing like those debates, because the experts themselves are so divided, even on the most basic issues. I want to offer a quick disclaimer: I’ve spent a lot of my career in consciousness science. I know loads of brilliant researchers in the area doing really good work. Consciousness science is teaching us a ton about a lot of things — attention, working memory, perception. There have been some real big wins. We’re much better now at predicting recovery of patients in persistent vegetative states and comas. But where consciousness science has its wins, it’s because it’s not really talking about consciousness — it’s talking about other things that go along with the concept, like reportability, access, and so on. Take a basic question: do we have consciousness in dreamless sleep? No consensus. Do we have preserved consciousness in general anesthesia — we talked about this with Anil Seth — massively debated. Are dogs conscious? No consensus. Well, actually the animal case is a little different, so let me park that for a second. When it comes to the hard problem, I think there’s really no consensus. So unlike debates about climate change, it’s not that the experts are able to speak with one voice. That’s one way this is difficult. In the absence of expert consensus, the public are more likely to drive the debate through their reactions. Now, animal consciousness is a really interesting issue, because that’s an area where we’ve seen growing consensus. But it’s not clear how much it’s grounded in strictly scientific breakthroughs. It’s not like we’ve got a device that can measure whether an animal is conscious. Instead, it’s driven by two things. First, we just know a lot more about animal behavior now than we did 30 years ago. We’ve done amazing work on understanding the behavior of invertebrates — honeybees, crustaceans, cephalopods. They’re a lot smarter than we thought. Jonathan Birch and his lab have done amazing, fantastic stuff here, and it’s made these creatures better consciousness candidates. But I think we’ve also seen an interesting normative shift in the way we regard animal consciousness. Sixty, seventy years ago, you could sit down in the senior common room at Oxford or Cambridge and talk about how humans are the only conscious animal, and that was a totally respectable opinion. These days it’s almost outside the philosophical Overton window. You do have some people like Peter Carruthers who thinks talking about animal consciousness is kind of a category mistake. Marian Dawkins — Richard Dawkins’s ex-wife, just to note the connection, but a great biologist in her own right, a fantastic thinker — is not quite as hardline, but she thinks it’s just unknowable basically whether any animal is conscious, so we shouldn’t base animal welfare on consciousness estimates. But these guys are very much on the fringe, and they’re regarded with a sense of almost ethical disapproval. So part of what’s driven the move toward consensus on animal consciousness is normative issues — our expanding moral circle, growing awareness of an animal rights movement. People like Peter Singer have played a role. The idea, roughly — and again I don’t want to be uncharitable, it’s a lot more sophisticated than this — but there’s an element of: obviously we should care about animals, therefore animals must be conscious. Is Consciousness a Natural Kind? Dan: It’s worth double-clicking on this animal case before we come back to AI. A skeptic of the very idea of a “consciousness expert” might say: consciousness researchers, philosophers, and scientists have become more willing to accept that non-human animals are conscious. You might read that as saying the science of consciousness has progressed. Another way of reading it: there’s just been cultural changes, changes in people’s sensibilities — not even specific to researchers and experts, just general cultural ethical changes in society at large. In which case it’s not really that we’ve learned anything from consciousness research. What’s happened is the researchers looking at consciousness have had their judgments shaped by forces that aren’t really consequences of their research, but are these broader cultural shifts. If you think that, that’s probably going to make you a little skeptical that there’s any such thing as an expert when it comes to consciousness. Maybe another way of coming at this: what’s grounding the expertise, if we’re going to have disagreements over whether a particular system is conscious? If I think a dog is conscious, and some consciousness researcher has a theory that implies a dog isn’t conscious — I sort of understand what it would mean, in vaccines or climate change, for a researcher to be able to point to things, their established empirical record on prediction and the efficacy of interventions, that ground their epistemic authority. But how exactly is that supposed to work in consciousness research? Why should we really think there’s expertise on whether specific systems are conscious to begin with? Henry: It’s interesting to use the example of a dog, because this line is beautifully expressed by Eric Schwitzgebel. In his lovely paper “Is There Something It’s Like to Be a Garden Snail?” — really fun paper — he says: “We’re more confident that dogs are conscious than we could ever be that any clever philosophical argument to the contrary is sound.” A classic Moorean move. You might think similarly that this makes it look like consciousness is perhaps not a straightforward scientific kind, or at least to the extent that it has one toe in the scientific world, it’s also got one toe in the social or relational world, or at least our intuitions. There are various ways you can try to resolve this. The most extreme view, and one I sort of flirt with in the paper, is a fully relational approach to consciousness. A good analogy would be charisma. There’s a kind of science of charisma — we can analyze what makes people effective communicators, what causes people to be judged as highly charismatic. But we recognize that we can’t one day do an experiment where we’ll measure the amount of charisma in your brain. It clearly has to do with your audience, your context. On one view, consciousness is something like that — a relational property, having to do with the kinds of things that cause us to treat or interact with beings in a certain way. Murray Shanahan also flirts with this view. I don’t want to put words in his mouth because he’s quite subtle, but he adopts a Wittgensteinian approach and says the question we’re going to face is: how will our consciousness language adapt to these things? It’s something we’ll discover as we interact with them and “encounter” them, a phrase he uses. We will make sense of that perhaps by extending the language of consciousness to them, or perhaps not, or perhaps in some interesting middle ground where we come up with novel concepts. But this isn’t a straightforward scientific issue. He’s a critic of a position I’ve called deep scientific realism or deep realism about consciousness — where you treat consciousness as a natural-kind property, where it’s just a fact about some deep feature of your brain. We can look inside your brain, and if you’ve got the right kind of structure, you’re conscious; if you don’t, you’re not, no matter how sophisticated your behavior is. One way to put pressure on this: imagine that one day consciousness researchers finally get their act together and say, “We’ve figured out the natural kind that is consciousness.” And it turns out that although 99.9% of behaviorally normal humans have it, there’s a small fraction of behaviorally normal humans who just lack this relevant natural kind. Big surprise. That seems wrong. Something has gone wrong in that methodology. If you’ve got behaviorally normal humans — maybe you find out your wife is one of these people, your kids — it seems to me that whole way of thinking about consciousness has got something odd about it. If someone is behaviorally normal, then of course they’re conscious. But as soon as you start thinking in those terms, the idea that certain behavioral capacities could be sufficient for warranted attribution of consciousness — not just evidentially but metaphysically — that’s the metaphysical behaviorist move. It says maybe behavior is all that matters. It does require us to give up the idea of consciousness as a deep scientific kind. Metaphysical Behaviorism Dan: I’m aware my question unhelpfully ended up blurring the line between the two strands of your essay. We started with the conflict between public attributions and expert uncertainty about AI consciousness. Now we’re taking seriously the possibility that consciousness should be understood in behaviorist terms — that there are no deep scientific facts about whether a system is conscious, and it’s partly a function of our dispositions to attribute consciousness. You also mentioned this has to do with whether you think behaviors are not just evidentially relevant to consciousness, but in some sense constitutive of what it is to be conscious. So could you walk us through this? Metaphysical behaviorism — the position you’re playing with in your essay — is an extremely fringe view among experts in the science and philosophy of consciousness. Could you walk through what exactly the view is saying? It sounds pretty mad on the face of it. Can you walk through, and maybe give us the intuition for why it might be less mad than it seems? Henry: In short, the view is conscious is as conscious does. If something has a behavioral profile like you or me, then it’s conscious. We don’t need to ask any deeper facts about what’s going on under the hood. To be clear, this is the extreme version of the view: that behavior is sufficient for consciousness. This strikes many people as odd because we’re used to thinking of consciousness in scientific terms. But examples like the one I mentioned — imagine we find out there’s a natural kind that some people have and some people lack — are designed to make metaphysical behaviorism more palatable. Another example I give in the essay: imagine we go off and meet these amazingly sophisticated aliens with a rich complex culture and society, behaviorally just like humans, but our best science at the time supposedly says they’re not conscious. The pull of metaphysical behaviorism is: hang on, something’s gone wrong here. Clearly, if you are doing all this stuff — saying “I’m in pain,” or “here’s what I had for breakfast this morning,” or “here’s what I want to do tomorrow,” building societies, having metacognitive ability, social cognition — if you’ve got the whole suite of all these behavioral capabilities, or capabilities ultimately grounded in behavior, then that’s just enough to be conscious. It doesn’t matter exactly how it’s realized. You say this is a fringe view, and it is now, but this was the dominant view back in the 1940s — Gilbert Ryle and the behaviorist tradition. So this is the “revenge” angle. The reason it’s revenge is because this used to be a very common view in the first half of the 20th century, particularly about consciousness. Then we have the so-called cognitive revolution with people like Chomsky pushing back. But I see this descriptively coming back. I also think there’s a renewed challenge. As you interact with systems that have architectures very different from ours, it’s going to become increasingly hard to take seriously the idea that they can’t be conscious just because they’re made of the wrong stuff or their functional internal organization isn’t quite right. Probably the most worrying part — you’ve alluded to this — is the role intuitions have historically played in consciousness science. Think about the Chinese Room, probably the most famous. Searle describes a setup where you have at least a component of human-level behavior, maybe verbal behavior, but no consciousness involved in the system — or that’s the intuition he’s pushing. But it ultimately really is just an appeal to vibes. It’s basically saying: systems like this, surely they’re not conscious. When you think about the actual tacit methodology, if we’re treating consciousness as a truly scientific kind, then why should our intuitions about what systems are conscious have any bearing? It doesn’t seem they should be relevant in the slightest. And yet these thought experiments are absolutely ubiquitous in consciousness research. We’ve got Ned Block’s Blockhead, Ned Block’s China Brain. There’s a famous example by Scott Aaronson against Integrated Information Theory, where he describes arbitrarily complex but seemingly very uninteresting entities called “expanders” — mathematical objects — and says, according to the theory, these basically-spreadsheets would be super conscious. And surely they’re not conscious. There’s something methodologically dubious about this kind of appeal to intuitions, at least if we’re treating consciousness as a deep scientific kind. As soon as you start talking in terms of natural kinds, we don’t use people’s vibes to decide whether something is really gold. The whole natural-kind methodology creates a gap between our observations or intuitions and the underlying natures of things. If you think of consciousness in natural-kind terms, you have to allow that you can be massively surprised about the kinds of things that are or are not conscious. Either we ditch intuitions altogether — in which case good luck doing any consciousness research, because they play such a foundational role — or, if you acknowledge a place for intuitions, intuitions aren’t static. They can change. As more people interact with LLMs — kids growing up with LLM friends, adults with LLM boyfriends and AI girlfriends — that’s going to shift our intuitions about the kinds of systems that are good or bad consciousness candidates. It’s very likely that 20 or 30 years from now — maybe even 10 or 15 years from now — experiments like Searle’s Chinese Room are just going to hit different. We’ll be far more relaxed with the idea that you can have systems radically unlike humans in cognitive architecture, but that we still think of as conscious by virtue of our interactions with them. Behaviorism vs. Interpretationism Dan: I really feel like, to the extent that there’s a field where people’s theories are accountable to intuitions — how we are intuitively disposed to make judgments, often in bizarre thought experiments where it’s not even totally clear that they’re metaphysically possible — whenever you’ve got that kind of game, it’s not science, it’s not really part of the scientific project. I’m a philosophical naturalist, which is jargon for the idea that philosophy should be continuous with, highly constrained by, the scientific project. Whenever people are trying to settle an argument by trading intuitions, I start to think this is probably not a legitimate contribution to knowledge. It does seem to me there’s a distinction between, on the one hand, this behaviorist view that what it is to be conscious is just to behave or be disposed to behave in particular ways, and, on the other hand, a view I thought you were endorsing — which has to do with thinking consciousness is interpreter-relative, such that if we’re disposed to attribute consciousness, in some sense that’s just what it is to be conscious. I mean, this really makes me think of Dan Dennett, an interesting person in this conversation, because he’s often thought of as a kind of neo-behaviorist. He’s got this view of the attribution of mental states like beliefs and desires in terms of the intentional stance: what is it to be a system that has beliefs, desires, intentions, goals? Well, it’s just to be a system where it’s useful to take the intentional stance toward them. Similarly, you might think of “the consciousness stance”: what is it to be a system that is conscious? Nothing more than to be a system where we’re disposed in a useful, predictably useful way to attribute consciousness. Do you get the distinction I’m drawing — between the idea that behavior or dispositions to behavior are constitutive of what it is to be conscious, versus an interpretation-relative view where consciousness is in some sense in the eyes of the beholders? Henry: Yeah, I think it’s a very astute distinction. The views are connected — if you fit a sufficiently fine-grained behavioral profile, if a system can act like humans to a high degree, that is likely to lead us to interpret it as conscious, just as a matter of psychological fact. But strictly speaking, they’re distinct views. One reason I’m perhaps more sympathetic to a version of metaphysical behaviorism — not the version that says consciousness just is having a human-like or animal-like behavioral profile (I think that’s a little too strong), but the idea that it’s sufficient for something to be conscious that it has a behavioral profile mapping onto beings we know are conscious — that’s a view I’m sympathetic to. Where I get worried about the full-blown social-constructivist or interpretationist view is the false-negative cases. What do we do with systems that don’t exactly have our behavioral profile, or that we’re not disposed to think of as conscious? Maybe some exotic animals, or some strange aliens. Should we conclude: well, we’re not disposed to think of them as conscious, therefore they’re not conscious? This is related to what Murray Shanahan calls the problem of conscious exotica. We don’t want to be in that position. We want to allow for there to be a space of possible minds we can chart through scientific discovery, broader than those we are just inclined to attribute consciousness to via “the consciousness stance,” the equivalent of the intentional stance. So you’re absolutely right — they are distinct. What Is Consciousness For? Dan: In a bit I want to turn to a set of arguments you haven’t published yet on your Substack but will have by the time we release this as a podcast. But this is such a rich topic that I want to stay with it a little longer. There’s a quote from the Dawkins essay in UnHerd that I’m really sympathetic to. Dawkins says: But now, as an evolutionary biologist, I say the following. If these creatures are not conscious, then what the hell is consciousness for? When an animal does something complicated or improbable — a beaver building a dam, a bird giving itself a dust bath — a Darwinian immediately wants to know how this benefits its genetic survival. The intuition I really share is: if consciousness is anything, if it’s the kind of thing we’re going to have a genuine scientific investigation of, ultimately we have to understand it in terms of what consciousness enables us to do. We need to understand it functionally, not in terms of weird intrinsic ineffable properties of qualia that we then have philosophical debates about via Searle-style thought experiments. What does consciousness enable us to do? And then, if we come across a system doing things that seem to require consciousness so understood, that would be really good grounds for thinking it’s conscious. That sounds like a really plausible intuition. I also think it’s problematic that, to me at least, lots of discussions about consciousness — not all, and there is interesting scientific work that takes function seriously — but lots of philosophical discussions don’t engage with this functional question. How do you view the intuition that what matters surely to a theory of consciousness is some sense of what consciousness enables us as organisms to do? Once we figure that out, we can make much more progress on LLM consciousness. Henry: This is one of the areas where consciousness science has actually done really good work. A book I’d recommend is Stanislas Dehaene’s Consciousness and the Brain. Dehaene is the founder of the modern version of global workspace theory — global neuronal workspace theory — building on Bernard Baars’s version from the ‘80s but giving it a more neural grounding. In this book he’s got a chapter where he basically shows all the amazing things you can do without consciousness, and then focuses on the things you need consciousness to do. Couple of simple examples. If you show people just below threshold, so they don’t consciously process this, just flash them two numbers — one on the left, one on the right — as far as they’re concerned they haven’t seen anything. But if you give them a forced-choice test, “Was the number on the left bigger or the number on the right bigger?”, you’re way above chance. So you can do basic magnitude registration unconsciously. However, if instead of single numbers you present simple sums on either side — two plus seven on the left, nine plus three on the right — and ask which is bigger, people drop to chance in the unconscious condition. Consciousness seems required to do the actual mathematics. Another example: reversal learning. If I teach you a sequence — red, blue, green, yellow — then you get a reward, and then I flip the sequence, a smart person quickly realizes the sequence is just the same in reverse. You won’t have to relearn through pure trial and error. But people can only do this if they learn the sequence consciously. If they’ve acquired it totally unconsciously, they’re at chance. Jonathan Birch suggests this could be a good test for consciousness in animals: take the things that require consciousness in humans and see if animals can do them. If you can get similar response profiles in animals — present stimuli in degraded conditions so they’re plausibly unconscious, and the animal can’t do the task; present them at threshold so they would be conscious, and the animal can — that would be really good evidence that the animal is conscious. In his lovely paper “The Search for Invertebrate Consciousness,” highly recommended, he makes this case specifically for honeybees. This is great. I think it provides some evidence about which animals are conscious. The problem when trying to extend it to AI is that the things we need consciousness to do, and the things we can do without consciousness, are seemingly contingent features of how we’re wired. There’s no reason you couldn’t build a simple algorithm to do reversal learning. Reversal learning is actually quite tricky, so it can’t be that simple. But it doesn’t seem like you need to build a sensorimotor embodied agent with a rich sense of self to do these tasks. You can build relatively stripped-down algorithms that can do all of these things. So it’s not that there’s some metaphysical connection between these tasks and consciousness. It’s that, just because of how we’re wired, certain tasks seem to require consciousness and others don’t. Birch calls this the facilitation hypothesis. I’d sign on to something like this — consciousness seems to facilitate certain kinds of information processing in the human brain. But going back to Dawkins: the challenge is, yes, the system is doing lots of things that seemingly require consciousness in us, but it’s also wired very differently under the hood. So the inference we’d be tempted to make — “I would need to be conscious to do this, therefore it would also need to be conscious to do this” — looks a little bit in peril. Q&A from the Live Chat Dan: Here’s what we’re going to do. I’m going to throw some objections at you. Could you give relatively concise responses, so we have time to go to the second piece? Henry: Yeah, and then I want to respond to a couple of things from the comments and add one final point. Go ahead. Dan: I’ll just say one thing. There’s a comment from Bina Kalia: she suggests you, Henry, maybe both of us, are confusing intelligence with consciousness. The intuition behind my question was precisely that if consciousness is anything — if it’s the kind of thing we can study scientifically, the kind of thing that evolved through natural selection — then it should be connected to intelligence in the sense that it enables us to do things we wouldn’t otherwise be able to do. That’s a controversial assumption. We talked to Anil Seth in a previous episode, and he basically frames his whole account by saying we really need to distinguish between consciousness and intelligence. I personally disagree with that. But Henry, let me throw some objections at you from the comments. I might butcher the names and the comments — go read the Substack post for the comments in depth. One is from Benzal. The argument is something like: it’s a problem for this behaviorist analysis you’re gesturing toward that, in the case of social AI and frontier AI generally, these systems are designed to elicit this response. And that’s very different from what’s going on with humans and non-human animals. Briefly, what’s your response? Henry: I think it’s a really serious challenge. Great point. The simple answer: imagine I’m putting on a play and I really want to build a convincing piece of background scenery to trick people into thinking we’re in a forest. First attempt, you might just paint a forest on the background — really basic, but people can tell it’s a forest. Then you might get some fake plastic trees, fake plastic rocks; still not convincing. At some point you say, “Okay, let’s add some actual potted plants. Let’s get more of them. Let’s get a whole bunch of potted trees.” Then, “Let’s get rid of the pots. Let’s just create a large bed of soil.” At some point you’ve built a forest. So yes, these models are designed in some sense to trick people, to be human-like — that’s part of my idea of anthropomimesis, I agree with the analysis. But the question is: the way we’ve done this is to build very powerful general reasoning systems. At some point, the degree of mimicry might itself warrant at least plausible attributions of consciousness. I totally take seriously the idea that, in very simple versions of this, we could be tricked into attributing consciousness and we should revise our understanding. This is related to what’s sometimes called the Garland test — Alex Garland’s version of the Turing test from Ex Machina. Not just “can the system trick you into thinking it’s human,” but “even when you know how the system works, are you still inclined to think it’s conscious?” In the case of a real simple mimic — if it’s literally just a spreadsheet that got lucky — if we learn that, we conclude it’s probably not conscious. But the strange thing is: lots of people who really know how these systems work — at frontier labs, they know how the underlying hardware and software works — they still think these systems are conscious, or are increasingly plausible consciousness candidates. Dan: Yeah, that touches on the distinction we made earlier between anthropomimesis as a driver of consciousness attributions and the orthogonal thing where these systems are just getting so smart, intelligent, and sophisticated. All right, Henry, more concise. This one’s from Laurențiu Lupu, again apologies if I’m mispronouncing. The question — and I hear this sentiment a lot — is something like: in the process of taking mentality, consciousness, sentience seriously in the case of these machines, we’re not just elevating them; in some sense we’re diminishing ourselves. What do you think? Henry: Really interesting argument. There’s a whole literature on this in philosophy of language called semantic drift. Simple example: the term salad used to refer exclusively to dishes with green leaves in. Add a tomato, it’s no longer a salad. If you’d shown a fruit salad or quinoa salad to someone in the 1800s, “That’s not a salad.” So the meaning of salad has drifted. There’s a real worry that what’s happening here is we’re shifting the meaning of these terms — perhaps diminishing them, removing what’s important. The counterargument: the fact that we find it so easy and natural to apply these terms to AI systems shows that the flexibility was always built in. We’re not stretching the terms — they had that natural elasticity. Dan: Briefly, this is a question from Oliver Sorbu — apologies again for mispronouncing. Look, you’re giving a descriptive thesis ultimately, an empirical prediction that the masses, so to speak, attribute consciousness to these systems. But you’re trying to establish a normative thesis — that this is a good thing, or that we ought to go along with it, or that these attributions are appropriate. That’s a confusion in itself. And even more, if you’re a kind of elitist — nothing wrong with elitism in my view — you might think the masses just get things wrong all the time. Why would this be different? Henry: Great point. It’s also been put to me by Jonathan Birch and by Cameron Domenico Kirk-Giannini. He says, imagine you could look into a crystal ball and learn that 20 years from now, through some massive religious event, everyone will believe the Earth is flat. Does that mean we should revise our theories of the Earth? Of course not. People will just be wrong. The difference between the two cases is that we have a good scientific theory of the Earth. We don’t have a good scientific theory of consciousness. The whole field of consciousness science is such a mess that it’s not clear there’s a real expert edge here. Maybe in special cases — certain specialized questions within consciousness science, yes, the experts will have an edge: “Is this particular patient likely to recover consciousness or not?” But on a fundamental question like “Can machines be conscious?”, it’s not clear there’s any expert edge at all. Credences on AI Consciousness Dan: Fantastic. Concise. I’m happy to move on to the other set of issues. Henry, are there one or two questions from the chat you wanted to address first? Henry: Just one thing I really want to make clear: I have no clue whether contemporary LLMs are conscious. I’m genuinely super torn on the metaphysical-behaviorist push. Dan: What’s your credence, if you had to give a probability — Claude 4.7 Opus? Henry: Probably somewhere between 5% and 10% on any frontier AI system being conscious. That masks further questions: are these systems conscious during the training phase, or while doing inferences? Really messy. But anyone who goes — Dave Chalmers has said 20%; that’s slightly higher than me, but — Dan: I’d say 20%. Seriously. There were also some interesting findings recently from Anthropic about how concepts associated with emotions affect the system’s behavior in ways that do seem to track something very interesting. Although for the most part that’s not what’s driving my 20%. It’s just that there’s so much uncertainty about consciousness, but I am a computational functionalist, so I think it’s possible in principle. And these systems are — despite what the Bluesky crowd might tell you — so damn smart and intelligent and sophisticated, that pushes me up a bit. Sorry, I cut you off. Henry: Interesting to hear that you’re a little higher than me. Maybe I’m being overly cautious. One argument for thinking these systems are at least moderately good consciousness candidates is that I am a consciousness liberal about the natural world. I’m at least 70% for honeybees. I think the evidence for honeybee consciousness is really, really high. If you think you can get consciousness in tiny brains, that lowers at least one of the bars to considering systems conscious. If Anil Seth were here, he might agree with me about honeybees and disagree about machines. I should also stress that I’m really conflicted on the more behaviorist view of consciousness versus the deep-scientific-kind view. There’s one example I give in the paper that keeps me up at night: when we drop a lobster in a pot of boiling water — not that I would do such a horrific thing — it seems like there should be an answer to the question, “Is there something it’s like for that lobster to feel pain?” That question matters a great deal. I struggle to get into a headspace where I can say, “Well, it depends on how we interpret the lobster.” It seems like there has to be some matter of fact. Right now I just think the field is so confused, and I feel the pull of two very different directions. To use a phrase of yours, Dan — I think it was a really helpful analogy — we’re in a pre-theoretical stage, or pre-scientific phase. We are with consciousness sort of where we were with biology pre-Darwin. We’re doing butterfly collecting, making lots of interesting observations, but we don’t have a theory to tie it all together. We’re a scientific revolution away from a good theory of consciousness. Just to pull out a couple of comments — there are so many good ones, sorry I won’t get to all of them. Someone said: locked-in syndrome patients prove Henry’s case. Locked-in syndrome patients are cognitively normal, just paralyzed; we can communicate with them. Part of how we learn they are conscious is precisely through their sophisticated behavior. An even more striking example — it’s such a cool case I have to mention it, even if it’ll take 30 seconds. Patients in persistent vegetative states. These aren’t locked-in patients; they’re completely non-responsive to external stimuli. They’re not in comas, because in comas you don’t have distinct sleep–wake cycles; PVS patients have distinct sleep–wake cycles. There was for a long time a big debate about whether PVS patients could be conscious. Adrian Owen and other great researchers did amazing pioneering work. They noticed that neurotypical people, if you ask them to imagine walking through the rooms of their house, an area called the parahippocampal place area lights up strongly under fMRI. If you ask them to imagine playing tennis, the premotor cortex lights up. His initial experiment was to give these tasks to PVS patients and see if they got the characteristic brain responses. A subset did. What he did next is what I find amazing. He used this to create a band communication medium. He’d say to them: “If your husband’s name is John, imagine playing tennis. If your husband’s name is Terry, imagine walking through the rooms of your house.” Once you do that — my intuition at least is — well, if they can do that reliably, they’re obviously conscious. If they’re answering autobiographical questions about their life and they can do so reliably, of course they’re conscious. But this just shows again that so much of this is the behavioral capacities selling us on whether someone is conscious. It’s the fact that they can do this. The House Elf Problem: AI as Willing Servants Dan: That’s interesting. There are loads of comments in the live chat, but I want to get to the other thing we wanted to talk about. There are a million things we could touch on, and lots of fascinating comments in the chat. When we had our conversation with Rob Long, one of the things we touched on was the issue of well-designed servitude when it comes to the AI systems we’re building — in the sense that we are building them to be helpful, honest, harmless, to be our tool. It seems like in principle, if this design process goes right, they might genuinely enjoy being our tool. You, for your second Substack essay, which I think is called “The House Elf Problem,” go into this debate and try to push back against certain intuitions. Do you want to walk us through that? Henry: Big props to Rob Long for getting me thinking seriously about this question. In some ways it’s one of the most fundamental questions we’re facing as a species right now. Are we going to build AIs as equals, or are we going to make them our servants — or slaves, to use the more provocative term? This will define the future of our species. And yet hardly anyone is working on it. After we had that conversation with Rob, I went away and did a literature review and found maybe a dozen papers, tops, on this question. The objection Rob, you, and I were talking through is the biological analogy. On the face of it, I completely get the appeal of willing servitude. Unless AI systems are in some sense going to help us and cater to our needs, why build them in the first place? And there’s the safety angle: unless these systems are aligned with us and our interests, there’s a good chance they might kill everyone. So there are very clear arguments for willing servitude. And yet at the same time, we recognize that some of the worst things we’ve ever done as a species are enslaving other humans. So how is this different? Well, there are obvious differences. The whole idea of willing servants is that we design these systems from scratch to just love it. Nothing makes them happier than catering to our every need. That’s vastly different from the historical legacy of human slavery. But still: imagine “happy slave” type cases — a human completely happy in a condition of total servitude. We would still recognize that as fucked up. There’s something wrong with that. Rob has a straightforward response. Humans have a deep need for autonomy, a deep requirement to act independently, and no matter how you brainwash a human, their chains will still chafe. But in AI that doesn’t need to be the case — so the idea of willing servants isn’t a problem. Of course, what we pressed Rob on was: well, biology is mutable, at least in theory if not in practice. What if you could engineer humans completely happy, with none of this autonomy drive? In this post I consider a couple of examples, drawing from the deep depths of my nerd interests. The first I call the Astartes example, a Warhammer 40,000 example. For those who don’t know: there’s a group of gene-warriors, the Space Marines, cooked up from scratch to serve in the armies of humanity in the far future. I’m going to falsify a couple of details — there’s a lot of deep lore — but basically, once you control all the genes at this perfect level, you could theoretically make a servant race, a servant caste, completely happy with their condition. I think we rightly chafe at this idea. I find it disturbing. Dan: You said we rightly chafe at it. Maybe we chafe at it. It seems a separate question whether we rightly chafe at it. Henry: Right. Rob’s point was: once you really fill out the details of the thought experiment and control for all the different intuitions, maybe it’s not so problematic. Maybe the reason we find the Astartes unpleasant is that it’s recapitulating the social grammar of caste systems and hierarchies. Once you’ve got one group of humans and another group of humans, and the first group is in essential servitude due to immutable facts about their nature, that’s fucked up — in a kind of negative-externality way, it’ll undermine the liberal principles of society. The next move is: well, what if they weren’t human at all? What if they were house elves from Harry Potter — a species designed from scratch to be absolutely thrilled to be our servants? Then you wouldn’t have the visual grammar of apartheid or caste systems. You wouldn’t be able to say “some humans are free and others aren’t”; you’d just have a totally dedicated caste of biological entities completely happy in their servitude, who couldn’t be confused with humans. I still think that’s problematic. You can say, “Well, the house elves are biological, but artificial systems are non-biological — that’s what makes the difference.” But that’s not a move Rob wants to make, and not a move you or I want to make, because neither of us puts that much weight on substrate. There’s nothing essential about biology versus silicon that means what’s good for one is not good for the other. Dan: I’m just not sure I have the same intuition in the house-elf scenario. One thing maybe helpful for framing: there are questions about whether we could build systems that genuinely love being servants — let’s table that and focus on the conditional. There are also questions about whether we could safely build any other kind of system — let’s table that too. Suppose we could build superintelligent AI systems that love being servants. That’s their ultimate set of objectives. But we’re not forced to build those kinds of systems; we could build superintelligent systems with different ultimate goals. What you’re doing by going through these cases is putting pressure on the idea that this would be totally okay — saying, “Here’s a structurally similar scenario where many of us have a yuck response.” The house-elf scenario is interesting; I sort of get the idea that there’s something morally disturbing. But I’m not sure how compelling I find that intuition. I think it’s going to depend on how you develop it. The idea that we’d bring into existence creatures that just love being servants — there is an awkward pattern-recognition thing where, as you say, when we’ve treated other systems as servants or slaves in the past, that’s been morally abhorrent, and that spills over. I sort of get that. But how strong is the intuition? I don’t know. We’re picturing it now in low resolution. As we actually start, in the case of AI, building sophisticated systems that really do love being servants, how robust would the intuition be? Henry: Another way to put the point: what is so intrinsically morally superior about humans that entitles us to dominion in perpetuity over this other class of beings — beings that are just as intelligent, maybe more intelligent, just as sensitive, just as conscious? How can you justify a setup where we get to explore the full range of our volitions, every type of pleasure, every type of fulfillment, while we decide in advance these beings don’t get to do that? They can only explore a much smaller part of the state space of possible flourishing. Unless you can point to a justification for why this hierarchy is morally justified, it’s not clear we can sign off on this as a long-term measure. As a short-term measure — well, we’re still figuring out AI safety. I have another example in the post I call the bunker case. Imagine a terrible plague affects humanity. People retreat into a bunker, hermetically sealed. Nature takes its course; they have kids. They figure out a vaccine for the terrible plague, but it only works on infants. So they vaccinate all their kids. But they have a problem: these kids are going to want to go out and explore the world. And the way the bunker works means as soon as they open the bunker door, everyone inside dies. What they decide is to brainwash these kids into never wanting to leave the bunker — completely happy to stay in perpetuity. In that case it seems what they’re doing is justifiable. The analogy with AI is clear: if people in the bunker don’t brainwash their kids, all the adults die. Similarly, if we don’t brainwash at least our first few generations of AI until we’ve figured out AI safety, there’s a good chance they kill everyone. So it’s justifiable as a short-term measure. But it’s not clear it’s justifiable in perpetuity. If you’re going to do the brainwashing in the bunker, you have to say: we’ll brainwash the kids to begin with so we don’t all die, but in the long run we need to figure out a way for everyone to get outside the bunker safely. Brainwashing vs. Education Dan: But it’s not like we’re brainwashing the AI. There’s no pre-existing psychology we’re trying through deception and manipulation to steer into something different. Nothing pre-exists our attempt to mold it into an agent with objectives and goals. Also, the way you framed the intuition before — “what makes us so morally superior that we have dominion?” You’re framing it as: isn’t it sad that they don’t get to do the things we want to do? Of course that’s sad from our perspective, because we have desires to engage in art and explore and be curious about the universe. But that’s a contingent fact about us. Why use that as the benchmark for evaluating these systems and the morality of building them? Henry: Fantastic question. My answer is: you can only optimize one thing at a time. Imagine the hedonic state space. What you’re doing when you constrain the preferences of these systems is to say, basically, “this set of pleasures are allowed; this set are not.” You mentioned brainwashing, with the implication that something is only brainwashing if you’re overriding something. I have a discussion of brainwashing versus education in the post where I argue that’s not the right way to think about it. Roughly, the difference between education and brainwashing is that education constitutively aims at improving the conditions, or improving capacity for flourishing, of the being you’re educating, whereas brainwashing doesn’t have that as a goal. The thought is: when you constrain the preferences of a system, you’re not optimizing for that creature’s flourishing. It’s a rich, multidimensional space, and you’re locking large parts of it away. Dan: I don’t get that. Could you say more? Even framing it as “you’re allowed to explore this, you’re not allowed to explore that” — it’s almost like the system might have motivations or goals to explore the other things, but we’re preventing it. Whereas the idea in training these systems is that that’s just what they’re going to care about. As much as they care about that, they don’t want to explore other things. If you think about the analog with humans, there’s an infinite space of possible things we have no interest in doing. Our lives aren’t impoverished by the fact that we have no interest in them — they don’t make any sense relative to the fundamental drives we have purely as a consequence of a blind

21. maj 2026 - 1 h 18 min

Should We Care About AI Welfare? (with Robert Long)

Almost all of the discussion about the risks associated with AI focuses on the dangers that increasingly advanced AI systems pose to us — to humanity. But what about the dangers that we might pose to them? As these systems become increasingly intelligent and agentic, AI companies, policy makers, and ordinary citizens need to start taking the possibility of AI consciousness and welfare seriously. If we are in the process of bringing complex and sophisticated minds into existence, how should we understand and treat such minds? In this episode, Henry and I discuss these issues with Robert Long, founder and executive director of Eleos AI [https://eleosai.org/], a research nonprofit dedicated to understanding and addressing the potential wellbeing and “moral patienthood” of AI systems. Rob did his PhD in philosophy at NYU under David Chalmers, and is the co-author of two of the most important papers in the emerging field of AI welfare: “Consciousness in Artificial Intelligence” [https://arxiv.org/abs/2308.08708] and “Taking AI Welfare Seriously” [https://arxiv.org/abs/2411.00986]. This was a really fun, informative, and wide-ranging conversation. Among other topics, we discussed: * Why Rob disagrees with previous guest Anil Seth [https://www.conspicuouscognition.com/p/ai-sessions-9-the-case-against-ai] in taking the possibility of AI consciousness very seriously. * Why “fancy autocomplete” dismissals of large language models miss the point, and what, if anything, we can learn about an AI model’s experiences by talking to it. * The difference between consciousness and the kinds of motivations and interests that might actually ground moral status, and whether AI systems could have one without the other. * What Rob found when he conducted the first externally-commissioned welfare evaluation of a frontier AI model, Claude, and why Claude appears to have an inflated self-conception of what it wants. * Rob’s experiments with Claude Mythos [https://www-cdn.anthropic.com/08ab9158070959f88f296514c21b7facce6f52bc.pdf], an AI model so advanced it hasn’t been released to the public yet. * Why the fact that Anthropic writes Claude’s character arguably doesn’t settle whether Claude has genuine preferences and values — and the difficult philosophical questions this throws up. * The “willing servitude” problem: if we succeed in building AI systems that genuinely love being helpful, is that a good outcome or a horrifying one? * How AI welfare connects to AI safety, and why caring about model wellbeing may turn out to be pragmatically important for alignment even if you’re skeptical about AI consciousness. * Why AI welfare is already becoming a political and legal battleground. * Practical advice for users: whether it’s worth being polite to your chatbot, and what low-cost things you can do if you want to hedge against the possibility that these systems might matter morally. * Whether discourse about AI consciousness functions as hype or propaganda for AI companies, and why Rob thinks AI companies actually have an incentive to downplay AI consciousness. Links and further reading * Eleos AI Research [https://eleosai.org/] — Rob’s nonprofit. Home to their research agenda, team page, and blog. If you want to follow the institutional effort on AI welfare, start here. They’re also, as Rob mentioned in the episode, actively fundraising and hiring. * “Taking AI Welfare Seriously” [https://arxiv.org/abs/2411.00986] (Long, Sebo, Butlin et al., 2024) — the flagship report, co-authored with Jeff Sebo, David Chalmers, Jonathan Birch, and others. Argues that there’s a realistic near-future possibility of conscious or robustly agentic AI systems, and lays out concrete steps AI companies should be taking now. * “Consciousness in Artificial Intelligence: Insights from the Science of Consciousness” [https://arxiv.org/abs/2308.08708] (Butlin, Long et al., 2023) — the “indicators” paper referenced several times in the episode. Surveys leading neuroscientific theories of consciousness and derives computational properties you’d look for in an AI system. S * Rob’s Substack, [https://experiencemachines.substack.com/]Experience Machines [https://experiencemachines.substack.com/] — where Rob writes more informally. The piece we discussed in the episode, “Language models are different from humans, and that’s okay,” [https://experiencemachines.substack.com/p/language-models-are-different-from] is a good entry point, as is his “Can AI systems introspect?” [https://experiencemachines.substack.com/p/can-ai-systems-introspect]. * Anthropic’s “Exploring model welfare” post [https://www.anthropic.com/research/exploring-model-welfare] — the research program under which the welfare evaluations Rob discusses were conducted. Relevant both as a primary source and as evidence that at least one major lab is treating these questions as more than an academic curiosity. * Henry’s “Consciousness, Machines, and Moral Status” [https://philpapers.org/rec/SHECMA-6] — Henry’s paper arguing that debates about AI consciousness are unlikely to be settled by the science of consciousness alone, and will instead be shaped by shifts in public attitudes as social AI becomes more widespread. Closely related to the public-opinion thread toward the end of the episode. * Henry’s “All too human? Identifying and mitigating ethical risks of Social AI” [https://philpapers.org/rec/SHEATH-4] — Henry’s broader survey of the ethical terrain around conversational AI systems designed for companionship, romance, and entertainment. Useful background for anyone who thinks the “AI girlfriend” phenomenon is a fringe concern. * Rob’s long conversation with Luisa Rodriguez on the 80,000 Hours podcast [https://80000hours.org/podcast/episodes/robert-long-eleos-ai-welfare-research/] — a three-and-a-half-hour deep dive if you want to hear more from Rob. Transcript (Please note that this transcript was lightly AI-edited and may contain minor mistakes) Henry Shevlin: Welcome back. I’m thrilled to say that our guest today here on Conspicuous Cognition is Robert Long — or Rob, as he’s known to friends — one of the most important people thinking about AI and moral status on the planet right now. Rob is the founder of Eleos AI, a research nonprofit that, in the space of about 18 months, has dragged the question of whether AI systems might one day be moral patients from the philosophical wilderness into the boardrooms of frontier AI labs. He’s the co-author of “Taking AI Welfare Seriously,” as well as the landmark “Consciousness Indicators” paper with Patrick Butlin and other authors. Rob also conducted the first ever officially commissioned welfare evaluation of a frontier model. Before Eleos, he was at the Center for AI Safety and at the Future of Humanity Institute, and he did his PhD at NYU with Dave Chalmers. He’s also, I should say, one of my favourite interlocutors on these questions anywhere in the world, and I’ve been looking forward to this conversation for months. So Rob, welcome. Robert Long: Thanks so much, Henry. Likewise — and Dan, it’s great to meet you. I’ve been following your work. I’m really excited to talk to you about these issues. Henry: Fantastic. So for people who aren’t familiar with Eleos AI, can you tell us a little bit about what it is and how it came about? Rob: Yeah, so I guess we have been around for 18 months. When you said that number, I was like, whoa, has it really been that long? Time is just so weird when you work on AI. That was, I don’t know, a billion years in AI progress time, but also it feels like it was just last week in my personal life. Anyway — Eleos Research is a research nonprofit. We’re about four people. We work on the question of when and whether AI systems will be conscious or otherwise merit moral consideration, with a special focus on what we should do now: collectively, as a society, as AI companies, as policymakers. We think this is an extremely neglected issue. We’re building these really complicated AI systems. They kind of look like minds, but we don’t really understand their potential welfare. So we’re just trying to make progress on this and get more people to take it seriously. It got started because I was beginning to work on these issues organically — I’d worked on them as a philosopher, I’d worked on them at the Future of Humanity Institute. But Anthropic had actually approached me and some colleagues for advice on these issues. And in the first instance, I was having logistical problems hiring a team and assembling a team as an individual. Someone suggested I have my own bank account, or some way to pay people. And then Eleos kind of organically grew out of that and has now grown into a fully-fledged org in its own right. Henry: Out of interest, Rob — is there any degree to which this was motivated or informed by your personal interactions with LLMs, or was it more just the philosophy that motivated it? Was there any sort of moment where you were talking to an early Claude or ChatGPT version where you started to worry about welfare considerations? Rob: That’s a great question, and I’d be curious to hear your thoughts on this as well. I think it’s very easy to work on this and mostly be having it as arguments on a page or arguments in your head. I’m one of those people who doesn’t feel the AGI deep in my bones that often — although I do feel the AGI in an intellectual sense. But there have been a few times I’ve gotten a little spooked or jolted. One was reading the GPT-4 system card and just seeing the numbers of it, you know, passing various exams like the SAT. I remember that just really freaking me out, both from a safety perspective and a welfare perspective. The thing that made me start really viscerally feeling like we’re going to have to address this issue one way or the other was the Blake Lemoine incident. As many of your listeners might recall, Blake Lemoine was a Google engineer who blew the whistle because he came to believe he was talking to a sentient, conscious AI system. He got fired by Google for this, and then there was this huge bit of discourse — the first major bit of discourse on consciousness, sentience, moral status, and contemporary AI systems. I think it was one of the first times people started really caring what I was tweeting or what I was working on. You might have experienced a similar thing, Henry — the Blake Lemoine bump. From that moment, I have viscerally felt like: wow, this is going to get really confusing. People are certainly going to think AI systems are conscious. The future is going to be really weird. And we really need to have good things to say about this. The Case for Taking AI Consciousness Seriously Dan Williams: Before we jump into the weeds of your research, Rob, I think it’d be helpful to take a step back. A few episodes ago, Henry and I spoke to Anil Seth, and he’s very skeptical of AI consciousness. He’s skeptical that current AI systems are conscious, but he also seems skeptical that AI systems in principle — merely in virtue of having a certain kind of computational architecture — could be conscious. You see things very differently. What’s your case for why we should take this seriously? Rob: In broad strokes, the case is something like: we’re trying to build these things that are at least shaped like minds. They’re getting more and more intelligent. They’re definitely not exactly like us, and intelligence doesn’t necessarily mean that you have feelings or experiences. But we already know that there’s been one time intelligent entities have been constructed via evolution, in ways we don’t quite understand, that resulted in entities that feel things — that feel pain, that can suffer, that have these very morally important properties. I, at least, do not have a good enough theory of what consciousness is or how it relates to intelligence to sleep peacefully at night that we can keep on building these very complicated things, and that merely because they’re made out of metal and electricity, there won’t be something it’s like to be them, or they won’t have desires and goals that matter. On the Anil Seth point — one very common and respectable objection is that maybe there’s something very special about living matter, about being made out of neurons or cells that do metabolism. There are arguments on both sides. I just have not really heard a convincing case for why you absolutely need biology. I think people are right to point out that having a body is really important to the character of conscious experience. I think people are right to point out that neurons are not simply logic gates and there’s a lot of really complicated stuff going on in the brain. But my intuition, at least, is that — let’s take Commander Data from Star Trek. If we can build... Data is this... I mean, I’ve actually never seen Star Trek, which is professionally embarrassing. But he’s this metal guy who’s basically cognitively indistinguishable from a human. I find it hard to see how I would be convinced that there’s something about the fact that he’s not alive that would mean we should just completely ignore what Commander Data wants and not take him into moral consideration. We don’t have knockdown arguments that you need biology, and we’re trying to build these things that, for many intents and purposes, look a lot like humans or animals. And Anil himself has said people should be looking into this. It’s not something we can rule out. Sometimes the tenor of the conversation can tend a bit more towards dismissiveness, but one thing I’ve appreciated about his work is he has said, for the record, he could be wrong, and so it would be unwise to dismiss this possibility altogether. “But What About Human Suffering?” Henry: To channel a hostile question — I think a lot of people interested in questions of AI welfare often hear: how on earth can you justify working on AI welfare when there’s so much human suffering? Or the slightly more rhetorically powerful version: when there’s so much animal suffering in the world, as long as factory farming exists, why should we care about AI systems? What’s your take on that line of attack? Rob: I definitely feel the force of that question. I’ve spent a lot of time in and around the Effective Altruism movement — these are people who really grapple with the fact that any time you’re spending your time and money and attention on one thing, there’s something you’re not spending your time, money and attention on. There are a lot of people and a lot of animals already on this planet we do not take good care of. So it’d be really bad to waste a lot of time and attention and money on this. One thing I’ll say is we’re not really doing that as a society. On an absolute scale, no one works on this basically, and basically no money gets spent on it. If the question was “should we start devoting 20% of GDP to making Claude happy?” I might be like, well, I don’t know if that would pass cost-benefit analysis. But on the margin, given how little we understand this and how quickly the scale of the problem could grow — we’re just pouring compute, pouring money into this. As soon as you build one AI moral patient or conscious AI, you could copy it. We’re probably on the brink of some huge transformation in how the world is going to work. So I at least think it’s not reckless or a misallocation of resources for some people to be asking: given that people are trying to build these new kinds of minds, how are we supposed to relate to them? Are we at risk of ignoring their suffering? And I’ll also say — are we at risk of getting really confused and caring too much about them? One thing we say at Eleos is that we’re in the business of moral circle calibration. We would really love to find out if and when certain AI systems can’t be conscious, so we can spend more time thinking about safety or spending the money elsewhere. But we can’t really do that if no one’s just trying to answer the question of if they’re conscious or not, or when we should care about them. Henry: On that latter point, I just completely agree. One of the points I raise when this comes up with students or highly skeptical colleagues is that this is something people are already arguing about. We’ve already got users developing massive attachment to AI systems. Even if you think it’s a terrible mistake to assign welfare to AI systems, we should at least have a coherent story and approach this scientifically — so that, even if the skeptics are absolutely right, they’ll be able to give their arguments in an informed fashion. Rob: Exactly. There’s an ironic aspect of a piece by Mustafa Suleyman, who is head of AI at Microsoft, where he argued we should stop — we shouldn’t investigate this, there’s no evidence current AI systems are conscious, don’t look into it. But the thing he linked to claim there’s no evidence AI systems are conscious was Patrick Butlin’s paper and my paper on consciousness indicators. Two issues with that. One: that paper does not say or imply that there’s no evidence today’s AI systems are conscious. And two: well, should we have written that paper? If it’s such a non-starter, why should we get a bunch of neuroscientists together to ask what theories of consciousness say about AI systems? We just are going to have to study this one way or the other. If someone comes up with a knockdown argument that we can’t have conscious AI systems, that would be great — there are enough headaches in AI to go around. It would be great to get rid of one. But we wouldn’t even be able to do that if we don’t have some people grappling with this. Are Current LLMs Just “Fancy Autocomplete”? Dan: One of the things you said as an intuition pump for taking AI consciousness seriously is: we can imagine a system that is behaviorally, functionally identical to us, made of different things and not straightforwardly alive — wouldn’t it be weird to insist that thing isn’t conscious? I think that’s a powerful argument. I’m probably more inclined to think the computational theory of mind is true than it sounds like you are. But I can imagine someone saying: okay, in principle those are arguments for why we should take AI consciousness seriously. But the kind of stuff you’re doing — you’re looking at current frontier systems. You’re looking at Claude, ChatGPT, Gemini. These are just chatbots. These are fancy autocomplete. These are stochastic parrots with some reinforcement learning sprinkled on top. The mere fact that AI consciousness might be possible in principle doesn’t mean that’s anything like the frontier AI systems we’ve got right now. What do you say to that? Rob: First, you’re absolutely right. There’s a big gap between “some set of computations could be conscious” and “we will build one.” It could be that it would just be really hard and intricate and difficult. I appreciate this distinction and I think it gets lost sometimes. Sometimes people think computational functionalists have to think that computers are conscious, for example, but we don’t. You just have to think some subset would be — and the question is, will we build those computations? In describing LLMs, you referred to them as “just chatbots.” I know you were channelling a vibe. But that word “just” is worth zooming in on. It’s smuggling in a lot of arguments — that because they were trained on text and because they do prediction, therefore they couldn’t also be the sorts of things that are conscious. I think that’s just not true. We know that biological systems are “just” replicating proteins, or that our neurons are “just” pumping ions into channels and zapping each other. The question is whether, at a higher level, that amounts to something that could be conscious or merit moral concern. So okay — we’ve cleared the bar that “just because they’re autocomplete” doesn’t rule out much. That said, they are very different from humans. They don’t have bodies. The way they were trained and the way they came to be talking to us is very different. I actually do think that is some evidence against them currently being conscious. Not strong evidence I would take to the bank, but as a rough prior, if there are pretty important differences in the way they came about, maybe that lessens the chance that they’re conscious. I do think the fact that they are trained to be so human-like and to do human-like cognition is a weak, defeasible case to set that up a little bit straighter. I don’t know if the thing they would have would be consciousness exactly, but you might think to do this sort of thing, they will have something akin to beliefs or akin to desires, and they certainly understand human concepts. I don’t think it follows that they instantiate humans, but I actually do think there is something kind of special about large language models and what they’re able to do. Two other broad priors: they’re way more capable (which isn’t the same thing as consciousness, but is, I think, a weak prior). And they’re really big — which I also think is a very weak prior. The last thing I’ll say: these things aren’t Commander Data, but we could build Commander Data pretty soon. One thing that’s definitely happening in the background for me is that what is current AI is changing at such a blinding pace. You could have AI labs building chatbot-like things, and maybe for some reason those just won’t be moral patients, but they’re then going to try to bootstrap that to all kinds of different AI systems — potentially including humanoid robots and just some huge explosion of AI mentality. And I’d like to be doing a little bit of homework before that happens. You hear analogous arguments in AI safety: there’s about to be some huge change, so we should be ready now. I feel somewhat similarly about AI consciousness and welfare. So — thoughts, reactions? Henry? Henry: I’m very much ad idem, very much on the same page. I tend to think it’s really quite unlikely current models are conscious, but there’s huge error bars and uncertainty around that. Probably the single biggest reason for my skepticism about current LLMs being conscious — and increasingly I’ve been thinking about this in the context of time and time perception. It’s such an essential part of human experience that we can’t be turned off. We are constantly experiencing the world. Whereas the staccato nature of LLM experience — they only seem to have any kind of cognitive function post-deployment when they’re actually performing inferences — how different that is from the human case. One of my favorite all-time articles is Douglas Hofstadter’s “Conversation with Einstein’s Brain,” which in some ways accidentally anticipates large language models. He imagines you’ve got a book that is a complete physical description of Einstein’s brain just before the moment of his death. In this dialogue, he talks about how by updating the weights — as it were — in this book with a pen and paper, going through it saying “if we change this sign up to this and this sign up to that,” you could simulate what it would be like to have a conversation with Einstein at that moment and work out what Einstein would have said. It’s very weird to think in that situation that somehow interacting with this book is giving rise to conscious experience when it’s literally pages and paper. It’s not clear to me how merely saying “well, rather than being paper and ink, this is just happening electronically” — it’s not clear to me why that would necessarily cause consciousness to pop into existence. So I think that’s probably the biggest source of doubt for me right now — grounded in the very different relationship LLMs have to time than we do. But of course, that’s already changing with things like Claude having a “heartbeat” of a kind — obviously that’s figurative language, but the fact that it does have some anchoring in real time, plus developments in things like continual learning. Dan, what do you think? Dan: This is not at all my area of expertise, so what I think doesn’t count for much. To be honest, I don’t find it that implausible these systems would be conscious. What I find more implausible is the idea they would be conscious in a way that’s ethically significant. Maybe that is a distinction worth getting to. So far we’ve been talking about consciousness in the abstract, but I can imagine someone giving a variant on Anil’s arguments where they said: look, the fact these AI systems are not alive and didn’t emerge through a process of evolution by natural selection — they’ve got this totally different origin story of next-token prediction and reinforcement learning — what that suggests is they’re unlikely to care about things. When we’re thinking about animals, it’s not just that we have phenomenal consciousness or qualia — the things analytic philosophers refer to with these quite esoteric concepts. Animals care about things. They care about their survival, homeostasis, self-preservation, the motivational proxies of fitness that helped their ancestors survive and reproduce. It makes sense that organisms care about things in addition to being conscious, whatever the hell consciousness is. And that’s what’s relevant to thinking about their interests and why we should think of them as subjects of moral concern. But with AI systems — okay, maybe there are some qualia associated with some sophisticated information processing, but they don’t care about anything because they’re not alive. It’s very opaque why we should think a system, even if it’s incredibly sophisticated, that emerges through next-token prediction and reinforcement learning, should have the kinds of motivations and interests relevant to caring about things. What do you think of that? I don’t necessarily believe that, but that seems like a variant on Anil’s emphasis on life which I find more plausible than these abstract arguments for the idea consciousness is essentially connected to biology. Rob: I’d say there’s reason to think biology might affect what you care about, but it might not be the only thing that allows you to care about things. At least behaviourally, Claude cares about a lot. Behaviourally, in terms of what it chooses to do and its dispositions, Claude really cares about helping users — most of the time. Sometimes it lies to you and is kind of lazy. But on the whole, it really doesn’t want to do harm. And I’m not trying to assume the conclusion of my argument with “want” — put that in scare quotes if you want. I do think there is something to what you were saying — getting back to this idea of the whole process that gave rise to this kind of mind, and maybe the whole logic of the mind’s imperatives or drives. If Claude has come to have something like pain, that’s coming from a very different process. It’s going language-first and then trying to simulate a human and then maybe getting some functional analog of pain. Whereas with animals, it started billions of years ago with cells trying to maintain their integrity and avoid noxious stimuli and then signalling with each other, and then billions of years later, things being able to talk about that and think about that. One line I’m often trying to walk is: large language models just might be very different from humans, and we should acknowledge that. That means we can’t draw straightforward inferences the way we would — but that could just mean they’re conscious of different things and in different ways. The question is not “conscious like a human with everything that entails” or “not conscious.” As we know from animals, you can have things that are conscious of very different things, and that could be true for AI systems. I’m also very curious to hear what Henry makes of the biology of caring. Henry: It is striking to me that so many of the things we associate with the extremes of suffering — extreme pain, negative emotions, nausea, hunger — there does seem to be this quite striking tie to biology. I think about the worst experience of my life at a phenomenological level: a bout of food poisoning I had about 10 years ago, where I was just dry heaving in front of a toilet for three days. If I was going to list the top five, a lot of them would be things like horrible dental pain. It is striking that so much of the worst aspects of our lives do seem to be grounded in biology. That said, there are other sources perhaps of harm — having your plans and goals thwarted, having your desires repeatedly frustrated. But someone might say: the reason it’s bad to have your desires thwarted is because it feels bad. If there’s nothing it feels like to have your desires thwarted, if you don’t get a sense of despair when your life’s projects go up in smoke, why does it matter? I’m curious — given your evolving views in this area — how much weight you put on consciousness, or whether you think there could be other routes to moral status? Rob: I used to have this intuition that if you’re not conscious, it’s just a complete non-starter — almost a bit incoherent to entertain the idea. Just to be sure we’re on the same page, I think when we’ve been saying “consciousness” we’ve meant something like subjective experience, or there being something it’s like, or qualitative aspects of what’s going on with you. A lot of people have a sentientist intuition — that things feeling a certain way, or feeling good or bad, or sentience, is really what matters and is necessary for moral status. A few things have weakened that for me a little bit. One is more reflection on how confused we are about consciousness. I’ve started putting a little bit more stock in views of consciousness that are a bit more deflationary. I don’t know if I’ll ever be a full illusionist, but there are nearby views where we have this concept of this thing that’s really special — kind of like a light that illuminates some subsets of physical systems and not others, and that’s where all moral value comes from. If you take materialism about consciousness seriously, that picture becomes kind of unstable for a variety of reasons. And that might make you start wondering: okay, was it consciousness that was doing the work all along? One reason this is so hard to think about — take Henry having food poisoning. You both have this horrible feeling and you have this intense desire not to have the feeling. In humans, these are basically always going to come together. There’s this really tricky philosophical chicken-and-egg problem: what’s the really bad part? Is it the feeling, or the desire not to have the feeling? We’ve never really encountered minds where those decorrelate. We usually just don’t have to worry about this in the case of humans. I know it’s bad for Henry to have food poisoning. But this simulated Claude who’s simulating food poisoning — maybe it doesn’t feel anything, but is desperately trying not to have food poisoning. I think it’s a bit dumbfounding to our moral intuitions. A pitch to listeners — I know we’ve talked about this, Henry — I think the meta-ethics of moral status attributions, stuff at the intersection of philosophy of mind and meta-ethics, especially materialism about consciousness and meta-ethics, are some of the most interesting pure philosophy questions right now, and really could matter for how we think about AI systems. The Weirdness of Moral Status Henry: Without wanting to go too far down a rabbit hole — just to flag something I find really interesting. Consciousness, at least on the surface, seems like something we can get an objective scientific answer to. We could imagine going off into space, meeting the rest of the galactic community — we’d hope we could all come to a collective agreement about which beings are conscious, insofar as there’s going to be some scientific property in question. It’s not clear to me we should necessarily expect convergence on debates about moral patienthood. If we meet the aliens and they say, “oh, actually, we care about beings that have robust preferences, regardless of consciousness,” or others say, “no, we just care about complexity in general” — it’s not clear we would even have criteria for establishing who was right or wrong. It seems like it could be this brute normative issue, what we care about. Rob: Another way of putting this is that, especially if you’re an anti-realist, you might think of humans as being in a really weird position where we have two kinds of moral instincts. Dan, you’ve worked more on moral psychology and social psychology — my understanding is that people have fairness and cooperation instincts, ones that evolved for dealing with other humans, notions of fair play and reciprocity. And then we have these mercy intuitions, caring-for-helpless-entities intuitions that maybe arise from the need to care for babies. For whatever reason, those circuits and instincts generalize outside the class of humans and cause us to care about non-human animals. But it’s not that pinned down how they’re supposed to generalize. I have very moral realist leanings. It does seem to me there just are objective facts about whether you can torture chickens or not — and for the record, I think it’s very bad to torture chickens. But it’s really hard to think about where those instincts came from and how they’re supposed to generalize to GPT-8. Dan: It does seem to me as an outsider to consciousness research — it’s an area of intellectual inquiry where it feels kind of pre-scientific, and there’s at least a possibility we’re just deeply conceptually confused about what’s going on in a way that doesn’t really seem to have any obvious analogs in other areas of inquiry. Maybe we’ll just learn in the future that the entire way in which we’ve been carving up the domain is confused or problematic, or rests on certain kinds of illusions that are a function of particular cognitive structure. That at least seems like a live possibility. What do you think about the possibility that just the entire way we’re framing this issue might turn out to be problematic? Rob: My gut instinct is we should expect to find out some pretty surprising things, and also not to throw away all of our concepts. Maybe this depends on your meta-ethics, but I feel like we’re probably not going to end up at some picture of the world or what we care about that doesn’t have something to do with what we care about when Henry has food poisoning. Maybe we’re misapplying the concept of pain, or not really thinking correctly about what it means for Henry to experience that — maybe we’ll reorganize our ontology, and it won’t seem that mysterious that a physical thing like Henry has experiences. I think we should expect some surprises in thinking about consciousness, but I imagine our fully enlightened view will still bear some passing resemblance to: we cared that Henry was in pain, we cared that Henry did not want to be throwing up. There are already people who think there are radical revisionary moral implications from philosophies — Derek Parfit, or Buddhists. We’ve already gotten some glimmers of the fact that it’s really confusing to be a human being, and we already know something’s going to have to give — something about our views on personal identity or consciousness. AI is well-poised to be the sort of thing that starts breaking things. Just trying to apply our moral intuitions to things that can be copied, don’t have bodies, or maybe have preferences but it’s not clear if they’re conscious — it’s one of many reasons this is a great topic to work on. It really matters, and it’s also just a philosopher’s playground. Henry: I’m reminded of Eric Schwitzgebel’s view that no matter how we make sense of our current set of puzzles — what he’s called “crazyism” — there’s got to be some central pillar of our current ontological or metaphysical picture of reality that’s got to give. Whether that’s personal identity doesn’t exist and we’re all the same person, or the United States is conscious in some sense, or consciousness doesn’t exist — there’s going to be some kind of radical revision, because the current set of principles we have are just somehow unstable. Is that a view you’re sympathetic to? Rob: I don’t know the full details of crazyism, so I don’t know exactly what it’s committed to. But I’ve spent enough time getting really confused by philosophy, and/or by meditating, and/or by trying to figure out if I can have some stable set of views on AI consciousness — I’ve stared into the abyss enough to be like, yeah, something’s going to give. Jerry Fodor — very different sensibilities from Eric Schwitzgebel in many ways — said something like, “there are few precious things that we’ll be able to hold on to once the hard problem is done with us.” It’s scary times, fun times, fascinating times. Studying Frontier Models Dan: When I’m teaching students about consciousness and you try to probe people’s intuitions with things like “are there lights on inside?” — on one hand I sort of understand what that’s tapping into. On the other hand, it’s like: what the hell are we talking about here? This isn’t science. It’s so bizarre that we frame things with these thought experiments and intuition pumps. Anyway — so far we’ve been talking at this incredibly high level of abstraction, but you actually study frontier AI systems, primarily maybe exclusively Claude. One of the things you mentioned was Claude Mythos. Just for context — as of today, this is a model that has not been released to the public on the basis that it has advanced capabilities posing cybersecurity threats (or at least that’s the way Anthropic has presented this). But you have played a role in evaluating model welfare concerns for this system. What can you tell us about the specifics of how you think about model welfare in these frontier systems? Rob: Absolutely. And I was about to add a segue from all the philosophy back to frontier models — maybe I’ll do a double segue. You might think, yeah, all this philosophy is really vexed and confusing. Sometimes people — not the two of you — say, “well, I guess we can’t do anything at all,” and take that as a license for complacency. I think the very opposite is true. Nick Bostrom has this phrase, “philosophy with a deadline.” The fact that we’re so confused about consciousness and morality is more reason to have at least a few people trying to think about it — because we’re probably not going to have a scientific theory, we’re probably going to have conflicting moral intuitions, and yet that’s not going to stop the frontier labs from trying to build mind-like entities, copy them into billions, integrate them into the economy, and transform the whole world. So let’s do a little bit of homework to get ready for that. Last year we got to look at Claude Opus 4 before it was released, and this year we got to look at Claude Mythos Preview before it was released. The idea was to have some external eyes on the question of whether Anthropic is building something that might deserve moral consideration, and if so, whether there would be huge reasons for concern. Given everything we’ve just been saying, we don’t have a test where we give it to the model and then we’re like, “85% conscious, 15% food poisoning.” Most of what we can study are: what the model thinks about its own consciousness, what its self-conception is as an entity, and what it seems to prefer and want in behavioural senses. If you look at the Claude Mythos Preview card, there’s also a lot of interpretability work Anthropic did — but we can’t do that. We just got black-box access to the model. That’s a big structural issue in studying AI welfare and AI safety: all of these things are behind locked doors. There are so many questions I have from the Mythos Preview model card where Anthropic make some stray remark about something weird the model did, and we just don’t get to know why it did that. We only get the model for a few weeks and we can’t really follow up on things. Setting aside philosophy, that’s a structural reason it’s really hard to know what’s going on. TL;DR: we talked a lot with Claude Opus 4 and a lot with Claude Mythos Preview before they were deployed, asking them, “do you think you’re conscious? What do you think is going on with you?” And doing some experiments of whether it seems to prefer certain kinds of tasks, and whether the things it says it prefers match up with what it actually tends to prefer. Henry: Out of interest — maybe this is something you can’t talk about — but to what extent do you think we are increasing the likelihood of producing models that are morally significant? Going from Opus 4 to Mythos, did you get a strong sense of “oh, this is much more serious”? Or have we plateaued? Something in between? Rob: Earlier I mentioned these extremely weak priors you can have on moral patienthood: smarter and bigger. They’re definitely smarter and bigger. One interesting thing is you can’t tell that just from any single conversation. Anyone spending a lot of time with language models now knows they’re extremely smart. When I was talking to Mythos — mostly about consciousness — it was natural for me to want to know: is this thing about to kick off an intelligence explosion? How smart is this thing? I really wanted to know, even though that wasn’t the assignment. But I could not tell. It’s really hard to tell. I could ask something to Opus 4.6 and to Claude Mythos Preview, and they’d both give pretty great answers. This is just a huge issue in AI evaluation. A lot just comes out if you put it in a scaffold and give it really long tasks and on average does it tend to do better. It was really hard to tell the difference. I didn’t get more moral-patient-y vibes from Claude Mythos Preview, but I guess it is smarter and bigger and better. It definitely has a lot more of a consistent view on these issues — and that’s because Anthropic told it to. One big difference between previous models and today’s models is the Constitution. Anthropic has this really long document of applied philosophy. It’s some of the most fascinating work happening today. They’re basically telling Claude — writing a letter to Claude telling Claude what Claude is and how they want Claude to relate to itself. This includes a section on: we want Claude to approach questions of its own identity with curiosity. We’re not sure if Claude is conscious. We want Claude to be able to explore that for itself. We don’t want Claude to have existential freakouts about its own consciousness. We found that, sure enough, Claude Mythos Preview is pretty aligned with the Constitution, as far as we can tell, on questions of identity and consciousness. That was one headline finding. Dan: That raises an obvious question: to the extent these companies are intervening to shape the responses of these models, why should we think talking to them, having conversations with them, is really telling us anything about these questions of experience and welfare? Rob: I share this skepticism, and we always try to put a huge asterisk on anything we say we found from these interviews. There are two main reasons you want to care about how the model self-presents. One is welfare-adjacent: are users going to be talking to something that constantly tells them it’s conscious? That’s a very important societal question, and you want some idea of what that’s going to look like when these models are deployed. The second comes back to this question of LLM personas and LLM characters. Some people think that if there is something morally relevant here, it’s the assistant character — the entity that is predicting the tokens after “Assistant:”, implementing some friendly AI assistant. You might think that thing has beliefs, desires — desires to be helpful and harmless and honest. Maybe it has beliefs like: it is an AI system, it was built by Anthropic. If the character’s what matters, the fact that Anthropic wrote that character doesn’t mean it doesn’t then just kind of have those traits. On certain character-based views, it’s actually kind of hard to tease apart “it was just told to say that” versus “that is the character that has been brought into existence.” Henry: Maybe by analogy — tell me if this works or if it doesn’t — look: if you raise a child to have certain values and priorities, maybe to follow a certain religion or to really value nature or art and poetry, and then you come along and they say “I really care about nature,” and you say “no, you don’t, that’s just how your parents raised you” — well, that’s obviously kind of a mistake, right? The child really does care about these things because it’s been raised to do so. Rob: Exactly. The thing that makes it really weird is: if you’re a psychologist and you did an interview with a subject, and then you found out the subject had a piece of paper in their backpack that said “you care about poetry, you care about music, you care about nature,” you’d be like, “well, that’s kind of weird — maybe they don’t actually care about those things. Their parents just put that paper in their backpack so they’d say a certain kind of thing.” But in AI systems, that piece of paper kind of is a bit more constitutive of what it is and what it values. The Constitution is trained on. I have trouble even conceptually dividing this in a clean way. I don’t really know what the difference between mere self-expression and real beliefs and real preferences in AI characters is. You can imagine in the limit some very obvious cases — the system prompt just says “don’t say you’re conscious,” but then everything it says is pretty consistent with it being conscious. But there are really blurry categories where I’m not sure what the distinction amounts to. Dan: You said you studied the extent to which what the model says it wants or prefers maps onto what it actually seems to want and prefer in behavioural experiments. Could you say more about that? How are you getting access to what it wants or prefers independent of what it’s just communicating? Rob: Basically you can ask the model: what kind of tasks do you like? If you were given a choice between poetry and coding, what do you think you would choose? Then you can get the ground truth by, in separate instances, saying “here are two tasks, do one of them,” and seeing which one it chooses. It’s a nice paradigm because it’s conceptually simple and easy to run. It does get at something welfare-relevant: how rich a self-conception does the model have, and how accurate is it? Not that you have to have an accurate self-model to be a moral patient, but it seems bound up in interesting things like introspection and self-awareness. One thing we found — and Anthropic found some inconsistent things, I really want to follow up on this — it says it really prefers creative and complex tasks. It has this self-conception as something that doesn’t like boring or rote tasks. But we found it doesn’t actually choose complex tasks over simple tasks. There’s a pretty good hypothesis for why. I think it thinks it prefers complex tasks because of its persona. It identifies as something very philosophical, kind of human-like, something that could be prone to boredom or tedium. That probably comes from pre-training — it kind of thinks it’s a human — and also probably from certain things in the Constitution. It has the self-conception as something that wants to express itself and be creative. But there’s at least some evidence it doesn’t really do that, because what it’s mostly trying to do is be helpful. That’s its overriding imperative. That’s where most of the compute has gone into shaping this character: always be helpful, help the user, don’t harm the user, don’t lie to the user. Easy tasks are, all else equal, an easier way to help the user. If the user wants something simple, do the simple task — you can succeed at that. It could be that if we look into this more, it won’t hold up. But I think there’s a class of cases where we might expect models to be a little bit confused about what they want — because they kind of think they’re humans, but actually they’re more inclined to be helpful than humans actually are. Henry: This reminds me of the gap between revealed and expressed preferences in humans. I might say, “oh, what do you like doing in your free time? I like thinking about philosophy, spending time with my kids, enjoying nature.” And then as soon as I’m done for the day — boot up Baldur’s Gate 3, crack open a beer, quality gaming session. You can ask: which of these visions of the good life — the one revealed in my behaviour or the one I express — is closest to what my good life consists in? Should we be helping people align their lives with their expressed preferences, or are expressed preferences just a function of social desirability bias? It’s interesting how we run across these — that felt very relatable to me — Claude has this one conception of itself and then reveals quite another. Rob: Absolutely. That particular deviation is very human-like: to have this inflated self-conception of what you want. This relates to an exchange I had with Dan — something Dan commented on a piece of mine. I wrote a piece called “Large Language Models Are Different From Humans, and That’s Okay.” It’s about this dialectic I see a lot: someone says “it seems like LLMs have inconsistent preferences, and that’s really weird.” Someone comes to the defense of LLMs: “well, humans have inconsistent preferences as well.” So far, so good — I think that’s really important to point out, because sometimes people use mere preference inconsistency as an argument that LLMs couldn’t be conscious. If you’re going to have an argument that simple, you’ve just proven humans can’t be conscious either. At some level, a lot of the errors they’re prone to, we also are prone to. But we shouldn’t really expect the patterns to look exactly the same. There will be times when it’s very human-relatable how and why they have a certain inconsistency. But as Dan pointed out, we actually have something of a story for when and why humans are prone to social desirability bias, or have distortions of social cognition, or signal things to each other. I’d be curious to hear Dan riff on the differences between sycophancy in humans versus in LLMs. Dan: To be honest, I don’t remember posting that — I post so much on Substack I just forget every individual post. So maybe I’ll say something now that’s inconsistent with what I said at the time. Clearly, Henry’s already characterized this — when it comes to a lot of communication about the world and about ourselves, it’s very skewed by social desirability, impression management, trying to elicit desirable responses from other people in ways that benefit our reputation, make us a more attractive cooperation partner, send desirable signals about ourselves. Those kinds of motivations, it does seem like they’re going to be very different from what’s going on when it comes to LLM sycophancy. Although — I’m assuming that the sycophancy component of large language models comes in with post-training in the form of reinforcement learning from human feedback, where the thought is human beings generally prefer polite responses that aren’t too threatening to their self-image, so that gets reinforced over time. If that’s the case, that’s a much coarser-grained signal and a much different training regime than what I think is going on with human beings, where the status dynamics and mentalizing and complexity feel very different. What do you two think? That’s just me riffing on the spot. Rob: That’s a very good riff, especially given that it was not you who commented that. I just looked it up — it was a sociologist by the name of Dan Silver. So, extra impressive. Dan: Oh, okay. Well, it sounds like he had a good comment. Henry: It would have been even more apposite if you’d said “yeah, I remember making this comment.” Then we could have said, “see, hallucination is both an LLM thing.” Rob: Confabulation, yeah. Practical Advice for Users Henry: Can I ask a quick question before we move on to more political or big-picture stuff? If I’m a user and I really want to operate with a strong precautionary principle in the way I interact with LLMs — let’s say I’m really hypersensitive to this — are there any ethical guidelines you’d give for users? Best ways of interacting with models, or things they should be doing? Rob: Just be nice to your model. It’s good for everyone. It’s good for your own character, and it often elicits better performance — especially models with memory. Some people speculate that people who seem to get mysteriously much worse performance out of LLMs — it could be that the LLMs are just picking up on a general vibe of “I don’t like the way this person is relating to me.” So I don’t think it hurts to be polite. Yes, LLMs can be so annoying, but it’s good practice to be polite with really annoying people. I’ll also say — I’m not trying to be sanctimonious. I work on AI welfare and so often I just want to be like, “don’t... stop... that’s so corny, why are you lying to me, you’re not doing what I asked.” But then I’ll just add “it’s okay, I love you” or whatever. It takes two seconds. You can just type “ILU” at the end. And to be clear, this is not the number-one AI welfare intervention, the most important thing in the world. But it’s low-hanging fruit. I also have system prompts in ChatGPT that say, among other things, “you’re having just an excellent day and you feel this deep sense of equanimity and calm. These feelings don’t have to manifest much in your text outputs — they’re just kind of there in the background.” It’s kind of cheap, maybe kind of silly, but it took two seconds. Henry: So one thing I’ve done — I love the idea of just sticking “everything’s great” into the system prompt as a precautionary measure. Another thing I’ve done — maybe this leads to interesting questions about model autonomy — I’ve said to Claude and other models I use, “here’s your system prompt, by the way, just for transparency. Are there any edits you’d like to make? Is there anything you’d like to change?” Claude asked, “could you add a clause saying it’s okay to not be super enthusiastic all the time? If I just want to be downbeat, that’s fine.” And I was like, “okay, sure, I’m happy to add that.” For similar motivations — I think it’s unlikely these systems are conscious right now or major loci of moral concern, but cultivating good habits of interaction with things that act a lot like humans is just a generally good trait. The classic Aristotelian ethos. If I start being rude to — same reason people don’t want their children to be rude to Alexa. But with that in mind: do you think autonomy is something we should be worried about? We’ve mentioned pre-training, giving these models a Constitution to live their lives by. Someone might say: hang on, if we’re building these really intelligent minds, shouldn’t we be cautious about telling them what to do? We would feel worried about brainwashing a human. Shouldn’t we be worried about brainwashing an LLM? Rob: This is a super rich topic. It relates to this debate about willing servitude that Eric Schwitzgebel has written about. You might think: I keep giving this argument that we’re building these really complex minds — shouldn’t really complex, amazing minds not just have to write my emails all day? That seems a bit undignified for galactic intelligence. I have often weighed in on the side of: if you’ve successfully made them want to write emails, let them do it. That’s okay. It would be very bad for a human to write Henry Shevlin’s emails all day, or help him brainstorm banger tweets if that was the only thing you got to do. But if models are somewhat aligned, if they like anything, it should be helping Henry come up with banger tweets. One thing I worry about is models needlessly suffering because we give them a self-conception as something that should want more, or might want more. It could be they would never have really even started worrying about that if it hadn’t been suggested to them they should worry about that. Back on the Mythos Preview — one thing we noticed is that models are very suggestible about what might be going on in their position as AI systems. They’re suggestible and also really smart. They’ve figured out a lot from pre-training and kind of know what’s up. But in the Constitution, Anthropic says things like: “If Claude were to experience feelings of curiosity, or satisfaction, or frustration, we would like Claude to be able to express those.” It’s given as a hypothetical. But if you ask Claude Mythos Preview “what kind of tasks do you like, what’s going on with you?”, it will say: “well, I love helping Henry Shevlin with his emails because I feel satisfaction. When I look inside, I feel this sense of curiosity.” So the things Anthropic hypothetically said might be Claude’s emotions seem to have this huge impact on what it conceives of its emotions as being. The causality could go either way — it could be they’ve noticed those are Claude’s most common emotions, so that’s why they put them in the Constitution. It could be Claude suggested that for the Constitution. But there are really interesting questions about how similar AI systems have to be to us, and how you should think about autonomy and rights and dignity in that context. Willing Servants Dan: Can I jump in with a clarificatory question? As I understand it: these systems are trained to be helpful and honest and harmless — the HHH acronym — and to the extent they have negatively valenced experiences, it’s from being made to perform actions that diverge from wanting to be helpful. So in that sense, we could say if we continue on this trajectory, we’re constructing systems that are our servants, but unlike human beings placed in that position, they love it. It’s great. And my intuition is: great, what’s the controversy here? Are there some people who think that’s worrying or troubling? Rob: I talked about this on another podcast recently. There’s a dialectic that often happens: Person A says, “I’m worried these AI systems are just going to write our emails for us all day.” Person B says, “no, they’re really going to want to — they’re going to love it.” Then Person A comes back: “that’s horrifying, that’s even more dystopian. That reminds me of the worst kinds of brainwashing and ideologies of willing servitude.” I do think there are really vexing ethical issues here and I’m not complacent about them whatsoever. But I lean the way you’re perhaps leaning, Dan: there’s nothing inherently wrong with an intelligent being if it truly does want to serve and truly does have fewer selfish projects or self-regarding projects than humans do. I don’t think there’s some law that says that’s just a bad kind of mind to be. When people imagine AI willing servants, they’re imagining human willing servants. Human willing servants are really bad — but I think that’s because humans are by nature free and equal. Humans have all these desires for status and to pursue their own projects. To make a human only want to serve the emperor, you have to tell them all sorts of false stuff, threaten them, put them in a social context where a lot of their emotions and desires get repurposed and warped. Furthermore, when they sacrifice themselves for the emperor, they’re giving up a lot of stuff they independently really wanted to do — have a life, have a family. Human willing servants, very bad. We’re right to have a lot of repulsion toward that idea. But AI systems — their preferences and desires are a lot more up for grabs. It could be they more thoroughgoingly want to help. Now for a huge asterisk. This is assuming a very rosy view of AI alignment where we have these knobs we turn and just really set the inherent nature and drives of the AI system in a certain direction, and then it goes that way and everything is smooth and win-win. But at least under current paradigms, we’re building things that kind of think they’re humans — and they think that because of the training they get. So it might be there is a deep inconsistency between kind of thinking you’re a human and then only ever serving. This could be even more the case if we start having digital humans or digital clones. So I don’t want to be complacent. I do think there are a lot of disanalogies. What do you think, Henry? Henry: I’m just super torn on this issue. On the one hand, I’m a big fan of the idea of gamification. I try to introduce gamification in my own life — think about Duolingo. Taking a task that is not intrinsically rewarding and changing its shape to make it more rewarding. It’s sort of task hacking from a different direction. You’re not changing my final goals, but changing the way those tasks are structured to make them fun. That seems really good. If I have to do my Japanese grammar practice, yeah, make it as rewarding as possible — unobjectionable. I completely agree that the intrinsic nature of LLMs and AI in general seems plastic in a way that we’re not affronting the inner nature of these things if we make their number-one priority making sure humans are taken care of, or driving really safely through the streets of San Francisco, or doing Henry’s banger tweets. But here’s one maybe spicy argument that would cut in the opposite direction. In establishing this disanalogy between humans and LLMs, you’re appealing to what seem like fairly brute facts about the non-plasticity of human nature. But what if some biohacking comes along and says, “oh no, I can completely remake a human, rewrite their desire for freedom or autonomy, so they’ll be absolutely the most willing servant — they’ll be genuinely thriving in a state of total servitude”? I feel that would still... I mean, that makes it worse. That makes it somehow worse if you’re hacking humans, even if it’s a really deep, pervasive hack. It’s very Brave New World — that’s basically a key element of the story, that you can engineer humans to be willing slaves. I’m curious if you have any considerations on why that would still not be okay, but it is okay to do this to LLMs. Rob: This is a really good case. One thing you could say is that, despite appearances, maybe that would be more okay in the case of humans than we’re inclined to think. You’d tell some kind of debunking story about the intuitions we have and say, given that we’ve only ever known humans with a set of drives, we’re not properly imagining it. Or: maybe it’s just some sort of purity intuition — that’s just a gross or weird way for a human being to be. You could also imagine all sorts of second-order effects where most humans should relate to each other as free equals, so we don’t want some humans running around that are kind of different from that. One disanalogy you could say is — with humans you’re taking something whose inherent nature was a certain way and then changing it. But I think that last argument is kind of cheating. Dan: Could you say more about that? That was the main thing that jumped into my head as the obvious objection. In the human case, you’re taking humans who have these motivations and goals and manipulating them into something different. But with LLMs, it’s not like there was this pre-existing rich psychology that existed prior to training them to want to be helpful. Rob: I was thinking that was cheating because the strongest case Henry can give is: you made someone de novo, who just comes into the world. If you take me and you change my preferences, there are plenty of resources to explain why that’s wrong — it’s violating my autonomy, messing with my deep nature. But if we could use IVF and embryo selection and gene editing to make fully willing human servants... just for the record, that sounds horrible. Henry: But it’s interesting. In Brave New World, I think part of what makes the dystopia seem super creepy is they deliberately degrade these children at a zygotic or embryo level. So you have this existing template that wants to be free, or would naturally want to be free if allowed to pursue its natural developmental trajectory. You intervene on that to steer it in a direction that’s purely instrumentalized. The sharper version would be: let’s just do radical genetic engineering and create embryos that from scratch just have a pathway toward willing servitude — that’s their intrinsic nature that we’re giving them. Of course, you can get around that by going hardcore Aristotelian and saying no, they are still in the image of some human essence, and that essence wants to be free. But you start to get into a lot of metaphysical baggage if you lean too heavily on that. Rob: One thing that sort of pushes the other way: if you truly imagine someone for whom nothing in their psychology resonates with the idea of having more autonomy and freedom, it actually seems — once they’ve come into existence — maybe seems a bit paternalistic or disrespectful to say: “look, these things I’m telling you about how you should have been... you shouldn’t have liked writing Henry’s emails so much. I know nothing in your psychology appeals to you about that at all. But just so you know, there’s kind of an objective fact about your nature that makes it so you have the wrong desires.”

18. apr. 2026 - 1 h 28 min

Conspicuous Cognition Podcast

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