# Generating Philosophy with AI — Talk Transcript Cleaned transcript of Nick's presentation and Q&A from the Lingnan–Genoa–Kobe workshop, 23 April 2026 (delivered remotely from Milan via Zoom). Companion to [[Generating Philosophy with AI — Argument Moves (Lingnan–Genoa–Kobe, 2026-04-23)]] and [[Generating Philosophy — Talk Speaker Notes (Lingnan–Genoa–Kobe, 2026-04-23)]]. Disfluencies (ums, errs, false starts) removed. Otherwise verbatim. Question-asker voices were echoey on the recording — their turns are reconstructed as faithfully as the audio permits and may contain small gaps marked `[unclear]`. Key figures and concepts referenced: [[Enrico Terrone]], [[David Davies]], [[Luciano Floridi]], [[Peter Lipton]], [[Timothy Williamson]], [[Wilfrid Sellars]], [[Maurice Merleau-Ponty]], [[Stevan Harnad]], [[John Searle]], [[Wittgenstein]], [[Inference to the Best Explanation]], [[Phenomenology]], [[Abductive Reasoning]], [[Chinese Room]]. --- ## Pre-talk **Chair:** All right, well hello everyone, welcome back. Our next speaker, as you can see, is joining us via Zoom from — Genoa, I presume you're in? **Nick:** No, I'm in [[Milan]], actually. **Chair:** Oh, okay. [[Nick Young]]. He works in philosophy of perception and AI and aesthetics and so on. And today he's going to talk to us about generating philosophy with AI. **Nick:** Okay, give me one second just to start my timer and share my screen. I think it's this one. Can you see my slides? **Chair:** Yes. **Nick:** And do they move when I do that? **Chair:** Yes. --- ## Introduction So yeah, thank you to the organisers for inviting me, and I'm very sorry not to be joining you all in Hong Kong — I'd much rather be there than on Zoom. Today I want to talk to you about some reasonably ambitious work. The idea is to try and say something quite strong, or quite interesting. This is work I've been doing with [[Enrico Terrone]]. We're in the process of developing this into a paper. I should mention — he hasn't seen the last week or so's changes on this, so he might want to disavow himself from some of the details. Just to try and get into the question — the research question, you can see there on the title: can LLMs produce philosophy worth reading? I'm going to talk to you a little bit more about this question in a moment, but the main part of this talk is going to be around three potential challenges to this idea, that LLMs could produce philosophy worth reading. I'm going to use "worth reading" as a stand-in. I'm not speaking at my most precise here, but I'm going to rely on you guys understanding what I'm getting at, because I think we can all understand — we all know what I mean if I say a philosophy paper or some philosophical text is worth reading. When you read papers, you hope that they are worth reading, and sometimes you're disappointed when they are not. You can elaborate this quite easily if you wanted to — I'm just going to gesture towards this stuff. Philosophy worth reading: it might be a compelling argument for a conclusion you might have otherwise rejected; it might be just something that makes you think, starts you thinking about concepts perhaps in a different way. These are the sorts of things you might mention if you say, this is a good piece of philosophy that I'm reading here. And of course, journals are aiming to publish papers which are worth reading. But of course, the stuff we send to journals that gets rejected — that is worth reading, and they're just making a mistake. --- ## Challenge 1: Authorship Okay, good. So I'm going to talk to you about what me and [[Enrico Terrone]] have been referring to as the challenge from authorship. We're talking about what counts as philosophy. What sort of — if, when you look at the text in your hand, if that was written by an LLM, should that count as an actual work of philosophy or piece of philosophy? In a way, this challenge is a little bit weird, because what we're trying to do is articulate an attitude we've come across in a lot of philosophers about the idea of AI doing philosophy. Not everyone, by any means, but quite a few — they kind of snort sometimes, or they just find the idea ridiculous: of course not. The authorship challenge is sort of trying to articulate that — well, obviously whatever they produce, that's not actually going to be philosophy. That sort of intuition. We're going to try and give that a bit more shape, and discuss it further. And then maybe tell you why we shouldn't go that way. Just on the final thing on that slide, you can see it says: philosophy as a person-only domain. No LLM text can be philosophy because no philosopher stands behind it. No philosopher has created it. What you might think here — here's an analogy. If you think about AI-generated art at the moment, I think this is a fairly common view: no matter how beautiful an image Midjourney or the new ChatGPT image thing produces, if it's purely in some sense AI-generated, it cannot be art. It can be aesthetically pleasing, but it cannot be art, because there's no artist standing behind it. And you might think, well, maybe something similar is going on with philosophical texts. Philosophical texts, or seeming philosophical texts, created by AI just can't be philosophy because there's no philosopher doing the activity. LLMs are not minds, they're not people, and so the text they produce cannot be philosophy. That's the intuition laid out. Now, one way me and Enrico have been discussing trying to flesh this out yet further is to rely on [[David Davies]]' idea about the relationship between artist and artwork — that line at the top: "the work is the philosopher's sustained activity, not the text she leaves behind" — or, in the artist case, not the art that she leaves behind. Here's another line from Davies. He says: "the work — what the artist achieves — is the process of eventuating in that product. They are rather intentionally guided generative performances that eventuate in structures of objects." So the idea is that on Davies' view, artworks themselves — the paint on the canvas — that's evidence of a performance, which was the creation of that artwork. When you're looking at the canvas, you are looking at it as the end product of a performance, and you're evaluating that performance. This allows Davies to say things like — if somehow something looking just like a Rembrandt painting suddenly came into existence, that would not count as a work of art, because no artist produced it. And that seems to get something right about artworks, at least. So one way you might want to flesh out the authorship challenge is to try and say something similar is going on for philosophy. The trouble is, it's really hard to get this idea off the ground if you think about it like this. Davies' ontology is trying to get something right about how people think about art, and think about artworks in relations to artists. As you can see on the slide now, we don't want to say the forgery and the actual Rembrandt are the same work of art, or anything like that. That's pragmatically how the art world works. Philosophy doesn't seem to me to be the same. Because you can imagine — choose your favourite piece of philosophy — imagine somehow those words had fallen together in some random process and just happened to have turned into a paper. It seems to me that that paper is still going to be philosophically valuable. You can think about this difference between art and a philosophy paper in terms of: the surface of an artwork underdetermines the work. There's more to an artwork than simply the paint on the canvas. In philosophy it doesn't seem to be quite the same. It's harder to make sense of that idea. There are maybe a few other ways you could try and make this work. Very briefly — for example, you could say, well, what about someone like [[Wittgenstein]] or [[Richard Rorty|Rorty]]? Wittgenstein, for example, would say, well, philosophy isn't the writing of papers; philosophy is sort of a therapeutic activity, something one does for oneself to reach some sort of philosophical good health, or something like that. And you can say — well, yeah, but even with these sorts of practice-based conceptions of philosophy, great philosophers such as Wittgenstein have still published texts, and these texts are still considered worthwhile to read. I don't think retreating to or adhering to a practice-based conception of philosophy is really going to save this. And of course, journals strip authorship before review — this is another reason why authorship of texts is sort of less important in terms of their value in philosophy. So that's my first challenge — the authorship challenge. That's about constitution, or what counts as a philosophical text. The next two challenges are more what we've been calling capacity challenges. There's nothing in principle which stops a non-minded system like ChatGPT writing worthwhile philosophy — ChatGPT or Claude or whatever — but they lack a certain something. They lack a certain capacity which humans have, which humans need to write the philosophy we write. --- ## Challenge 2: Abductive reasoning Let's look at the first one, which is about [[Abductive Reasoning|abductive reasoning]]. So this is a paper by famous Italian philosopher called [[Luciano Floridi|Floridi]]. And he argues that LLMs do not do abductive inference, or inference to the best explanation, in the way that humans do — really in any way. Humans can abduce; but according to Floridi, LLMs cannot abduce, despite perhaps giving the appearance that they can. This seeming abduction but not actual abduction, he names "zeroth-order abduction". Here's another example — not on the slides — about what Floridi is getting at. You can ask an LLM why a car won't start on a cold morning, and it might say something like: dead battery, cold weather reducing efficiency. Which sounds plausible, right? That could well be why your car is not starting. But what Floridi is saying is, if you ask a human that, they might actually do some abductive reasoning. They might say, well, what are the possible explanations here, and what seems most plausible? You might take different bits of evidence into account — I don't know, how cold it is, the age of your car, this sort of thing — and use it to generate this plausible inference to the best explanation. What Floridi is saying is, when you ask an LLM that and it spits out "dead battery, cold weather", etc., it might seem like a plausible explanation, but it hasn't done any of the inference to the best explanation that a human would do. I'll just read you another little quote. He says: "LLMs seem to perform a kind of zeroth-order abduction. Given a prompt, they generate a plausible continuation based purely on learnt associations about what tokens come next" and these sorts of things. "The model does not understand what an explanation is, but it produces text that follows the typical phrasing and structure of explanations. It doesn't reason about causes from scratch, but outputs typical causes for typical effects observed in the training data." You might think this is a problem for philosophy, especially if you're someone like [[Timothy Williamson|Williamson]], who thinks one thing philosophy does a lot of is abduction — compared to, for example, science. So you might think, well, if philosophy is a lot about inference to the best explanation, trying to understand how things hang together in the broadest sense of the term, this sort of stuff, then you might think that abduction seems to be really quite important for philosophers. So we've got these two things together: LLMs can't abduct, potentially; and we have at least some people in philosophy saying a lot of philosophy is about abduction. So how are we going to avoid this challenge? First thing to say is, I'm not going to try and convince you that LLMs actually do do abductive inference. I don't think that's going to be — that's a non-starter as a solution here. So the idea instead is to look at how LLMs are trained and how LLMs work, and the corpus of philosophical texts that these things will have consumed, and then make an argument as to how this sort of training, we might think, would lead to the capacity to produce text which has the properties of good abduction in the text, despite not being a product of actual abductive reasoning. Trying to explain that to you a little bit better. If you think about all of the text that's been stuck into an LLM in its training, it's going to have a lot of philosophy in there. And that philosophy uses an enormous amount of explanation language. I'm going to skip this slightly — sorry, one moment. Yeah — so if you think about it, we have a lot of explanation in philosophical texts that have been consumed by LLMs, and patterns are predicted on the basis of how these argument words are used, as it were. A lot of philosophical work is done on the page, you might want to say — in the prose itself. You're handling objections, you're looking at virtues, and things like that. Floridi himself will say that the reason why an LLM can produce plausible-looking hypotheses is because they're trained on data in which plausible hypotheses are worked towards, are shown in the text, examined in the text, and proven in the text. I don't want to go too long on this because I think I'm running slightly behind. But briefly — there's a book by [[Peter Lipton|Lipton]] called [[Inference to the Best Explanation]], and he's talking about two ways you might think about properties an explanation can have. It could be the most likely explanation, and it could be the most lovely explanation. Likely explanation is about probability — given the evidence, how probable is this hypothesis? Loveliness, on Lipton's account, is about explanatory power. If the hypothesis were true, how much understanding would it give? How elegantly does it unify? How much does it illuminate? And the two can come apart. A conspiracy theory that posits a man behind the scenes sorting everything out — that would be lovely if it were true, because it would explain everything in one fell swoop, but it doesn't make it very likely. So you can see how these things move apart. However, Lipton does think that loveliness is a guide to likeliness. The lovelier an explanation, the better it explains things, the more probable it is. He has various mechanics about how this works. Why this matters about LLMs: over an arbitrary corpus, statistical probability has no connection to explanatory power. But over a philosophical corpus, filtered by what philosophers have found explanatorily valuable, statistical likelihood ends up kind of approximating loveliness. Very briefly now — like I said, I don't want to get too bogged down in this. If you think about the process of refereed and cited and published work, you can think of this as acting as something like a filter on what sorts of arguments survive and are more likely to be represented in the corpus that an LLM is trained on. So the idea is that LLMs would have been statistically exposed to good philosophical arguments and good analyses of philosophical arguments, and somewhere latent inside them have this information statistically represented. And just one more little link on this. Sometimes, if you ask an LLM to think step by step, you'll see it use words like this and try to analyse its own reasoning — "the stronger reading is", "one might press the connection", etc. Basically, when you make a model think step by step and it reasons better, what it's doing — or rather what you are doing — is taking advantage of the statistical likelihood that these thinking words, arguing words, explaining words will force the LLM, will make the next token more likely to be a word that is the most lovely and likely explanation. So this brings us to the end of the second challenge. I've got one more big challenge to do. Just to recap: what I've tried to argue there is that while LLMs lack the capacity to do abductive reasoning, they are still capable of producing text which is likely to have the property of having good abductive reasoning within it. --- ## Challenge 3: Phenomenology Now we're going to look at a different sort of challenge — also a capacity challenge, something that LLM systems can't do or don't seem to have. And that is [[Phenomenology|phenomenology]]. What you could do here is make the following argument. You could say: look, obviously not all philosophy starts from phenomenological experience by any means, but you might say, well, look, an LLM, which doesn't have phenomenological experience, is not going to be able to do any sort of philosophy which does require reasoning or thinking or inferring from phenomenal experiences. And you might say, well, that's maybe not all of philosophy, but if you think about how common phenomenology is in something like mind, or aesthetics, or perception, or many, many other things, that's all going to be off-limits for LLM philosophy because it doesn't have the capacity to have phenomenological states. The way we're trying to make sense of this argument is to look at a paper from [[Zahavy]]. Not the Danish phenomenologist — but, I believe, a computer scientist who works for Google DeepMind. He has a paper called "LLMs Can't Jump", and if you're old enough you'll get the play on words for the movie name. He gives us the example of Einstein. So — actually, let me start back a little bit. Some arguments, Zahavy calls "need the felt experience an LLM never has", and he calls this manipulative abduction. It's inference via simulated sensory experience, or by actual sensory experience. He gives this Einstein example. He says: "Einstein envisions a physicist inside an elevator being uniformly accelerated through deep space. Inside the enclosure, the sensory experience reveals a specific pattern. When objects are released, the floor rushes to meet them. Thus the simulation," says Zahavy, "was not a permutation of symbols but a manipulation of perceptual experience." The idea would be that an LLM would never be able to have some sort of breakthrough thought experiment such as Einstein's elevator, because Einstein started from phenomenology, not from symbols, or permutations of symbols. Building on this a little bit, he takes a [[Stevan Harnad|Harnad]]-like view. He says: well, maybe LLMs are just high-dimensional [[Chinese Room|Chinese rooms]]. We all know [[John Searle|Searle]]'s Chinese room. Harnad says, basically, what an LLM might be doing is just manipulating the language of physics, manipulating language about the world, without having access to any of the physical referents that give it that meaning. So you can think about them as being somewhat similar to the classic Searlean Chinese room. You might think — well, this is all, Zahavy is not talking about philosophy specifically — but we might say, well, something very similar could be levelled at LLMs doing philosophy as well. Imagine — you might say, well, an LLM is never going to be able to give us a cool thought experiment like Mary in the black-and-white room, or something like that, or the missing shade of blue, along those lines. And that's because LLMs don't have these sorts of conscious states. Just to emphasise: it doesn't have to just be perceptual states. You can see on the slide there — someone like [[John Bengson|Bengson]] might say there's a feeling of intuition, this experiential feeling of intuition. I've been interested in the other two as well — I'm interested in the experience of feeling yourself as an acting agent, and how that can be linked to the feeling of time passing. And you might say, well, LLMs just aren't going to have anything interesting to say here, because they don't have these sorts of states to start from. So what am I going to say here? Same sort of slippery argument, in a way. I'm not going to tell you that LLMs really do have phenomenological experiences, nothing like that. But what I am going to say is: science and philosophy link up to the world differently, and this allows LLMs to avoid having to have phenomenological states themselves. What Einstein did — it gave Einstein this idea for the equivalence principle as a hypothesis about the world. And then later on, physics got there in the end with Eddington and Mercury and things like that. So that's the role of, in our Einstein toy example, what the thought experiment did. Philosophy, we want to say, is doing something slightly different. It's not about creating hypotheses we can experiment on in the world. There's a paper by an American philosopher whose name is [[Pigliucci]]. And he says: well, the world figures differently in science than it does in philosophy. We've just seen the Einstein one — Einstein was making a hypothesis about the world itself. Whereas in philosophy, it's not about creating hypotheses about — that we can experiment in the world. What I mean by this is the following. As you can see on the slide, the challenge is no longer whether an LLM has phenomenological experience; it's whether it has access to articulated descriptions of that experience. What I mean by this is simply: passages in the corpora that the LLM has ingested which talk about perceptual experience, or the experience of moving through time, or agentive experience. The idea with Pigliucci is he would say: well, what phenomenological experience is doing in these sorts of cases in the text is, it's being used as an axiom. It's being used as a place to elaborate from. So if we start from the Mary or Chinese-room example — what we do there is, rather than having to come up with this idea ourselves, the text itself serves as an axiom from which to work from. If you think about philosophy of perception, about how things look, about temporal experience, all of these things — and you can also think about literary writing — the corpus that LLMs are trained on is steeped in articulated phenomenology. And the idea is that in this training data, in the philosophy, we then see these articulated phenomenological descriptions being reasoned about by — using the sorts of words and processes that we saw in the previous challenge. So the idea is that we're not having to, as philosophers, closely examine what it is like to experience red in the Mary case, but rather using standard claims we might make about how phenomenological experience is, and then reasoning from them. Just to make this point a little bit clearer: an LLM has never experienced weightlessness as a lift goes down, or anything like that. But what it does have is passages in fiction about such a thing, or astronauts' memoirs, or things like this. The idea here would be: this serves as enough to be able for it to do a great deal of phenomenology-based philosophy. Just briefly, here's a little piece of anecdata for you. These slides I've designed with AI, and I've chosen colours with AI. If you talk to an advanced AI now, it will be able to have extraordinarily sophisticated discussions with you about colour matching, and about line spacing, and about putting letters on separate lines or in the same line, etc. It will talk to you in a very realistic facsimile of someone who really has had these colour experiences. So this is what I think an LLM can do to avoid the charge of not being able to do phenomenology-based philosophy. Now, just briefly, I want to suggest a limit to this. It seems to me that one way you could say that LLMs can't do what a human might be able to do is: discover new aspects of phenomenological experience. So, here's the toy example I like, which is [[Maurice Merleau-Ponty|Merleau-Ponty]] on self-touch. I think it's in the *Phenomenology of Perception*. He talks about — your fingers on each hand touching each other — and he makes the observation that you can only ever have one toucher and one touched. They can switch — your right might be the touched and the other one might be the touching, or they can be the left and the right — but never both touching themselves, or both being the touched, as it were. If we assume that this was a genuinely new phenomenological discovery, we might think that this is outside of an LLM's wheelhouse. But then, once that example gets into the literature and is discussed, we might think that it would also be reasonably easy to be subsumed into the capacities of an LLM. How am I doing for time? Can I get five more minutes? I know I started a little bit late. Okay. --- ## Section 4: Where are the great LLM texts? So move on to four. Four is a lot more tentative in some ways. So it's kind of this question: I've given you three reasons, in the form of my responses to those challenges, to think that maybe LLMs can produce philosophy worth reading. And then you might say, well, okay then, show me where these great LLM texts are. Why aren't there any great LLM texts being written now? Notice that I'm not saying in the future LLMs will be able to do this — I'm saying about the models right now that they should be able to give us something worth reading. So you might say, well, where are they? What I think the issue is here — it's not a matter of the capacity of LLMs to produce good philosophy. It's more a matter of our ability or our knowledge as to how to extract this sort of information. I'm sure plenty of your students have typed in: "explain the Mary argument, give me some arguments against it", this sort of stuff, and you'll generally get quite dubious, flat, clichéd, possibly plagiarised prose — survey-style, hedged, balanced, telling you how interesting it is. This is not worthwhile philosophy. What I think we need to think about more is how to get at these capacities as philosopher-prompters. So I've tried to argue, especially in maybe sections two and three, that the philosophical corpus was produced by many rounds of arguments and counter-arguments, each paper written by somebody reading earlier papers, building on this sort of stuff — and the idea would be: strong work survives. So we might say that the corpus is the distillate of this process. It's supposed to be the *crème de la crème* of reasoning, in some ways. And an LLM trained on this corpus inherits this, distilled, in statistical form — the surviving patterns, the best handling of objections. But inheriting the distillate is not the same as performing the distillation. The distillation is a temporal process — you've got to get the LLM to produce this thing by running the right sort of prompts on it. Sorry about that slide. Oh well. That's just the [[Wilfrid Sellars|Sellars]] quote — you know it very well. So basically, like I said, this is very hand-wavy, very speculative to end here. All I'm saying is: maybe we need to think of LLMs as distillates, and we need to be able to extract good philosophy from now. One more thing about prompting, just to talk about: arguably, the way we might want to think about prompting these systems is to try and make use of the sorts of words and phrases I mentioned before — the argument and explanation words. "So", "therefore", "this is a clear objection", etc., etc., etc. So rather than just asking these LLMs philosophical questions, the idea is to *elicit* good philosophy from them. And just a very final thought, just to throw it out there: occasionally I'm asked whether it would be a good idea to train up a specialised LLM specialising in philosophy. The reason you might want to ask this is there's been some success with mathematics and LLMs, training up specialised mathematics proof generators. So you might think, well, specialisation might work well in philosophy as well. This is not so much an argument as maybe a potential to resist this idea. So despite what I'm trying to push with these argumentative words and phrases, and hijacking that part of the language with these systems — it also seems to me that, well — I'm generally a Sellarsian about what philosophy is, which is: "the aim of philosophy, abstractly formulated, is to understand how things, in the broadest sense of the term, hang together, in the broadest possible sense of the term." So it seems to me that maybe we shouldn't be moving towards specialised philosophy LLMs, but rather take advantage of their reasoning capacities while still using general knowledge in order to have this general hanging-together of everything. And with that, I think I will close. That's just a summary of what I've said. We have at least 20 minutes for Q&A, maybe a bit more — super tops on the late, as usual. Hand over to the chair for the personal favourite part. --- ## Q&A ### Q1 — on chain-of-thought and the Apple paper **Nick:** Hi — could you give me one second, just to get a notepad up on my screen? Hold on. Yeah — actually, no, don't worry about it, it's fine. Anytime you like. **Chair:** [trying to get a working microphone] It seems to be a general problem. **Q1:** Great, thank you so much for the talk. I felt it was really interesting. I thought you brought up the point about prompt engineering at the very end, because that seemed to be the most likely way it could be used to elicit good philosophy. So that was going to be my initial question — that seemed to be missing from the paper, and then you [unclear] my idea, which I was happy about. I just wanted to reflect on one part that you said, and ask you about the significance you think it holds for LLMs contributing to philosophy — the step-by-step process in particular. So my understanding of the step-by-step process in large language models, and how you can give them a listing of thoughts — through studies done recently, both by Apple in the industry and [unclear] studies, showing that chain-of-thought elicitations can actually sometimes be incorrect but still generate correct outputs. So there's a dissociation that occurs between chain of thought and the output that actually generates. There's the Apple paper, and there's a paper [unclear] talking about — where the LLM is describing how it arrived at its solution and gives you the correct solution, but if you look at how it breaks it down against chain of thought, it actually doesn't follow up. So the chain of thought is divorced from the actual output. So it's just the illusion of chain of thought — it's not actually following a reasoning process. I'm just wondering what you think about these recent studies that show that chain of thought is not an indication of [the model] actually tracking something with something. **Nick:** Okay, good — thank you. Nice, crunchy questions to start with as well. So thanks. I'm only familiar with the Apple paper there. I have a vague memory that a lot of people didn't think that paper was very good, but I'm not going to try and attack the paper — so assuming that this is correct, that sometimes the conclusion is not derived from the actual chain of thought. A couple of things here. One is, I guess I could rely on the Deep Thought joke from *Hitchhiker's Guide to the Galaxy* about the answer to life, the universe and everything being 42 — and the joke is that it's meaningless because they don't know what the question is. So maybe one way I would respond to this would be to say: well, when I'm talking about worthwhile philosophy, I'm not talking about the conclusion, or just the conclusion. I'm talking about a larger chunk. And I'm trying to talk about eliciting this larger chunk of actual reasoning to an actual conclusion. So I wouldn't want to — rather than just asking philosophical questions and getting this answer without checking the reasoning, I think philosopher-prompters should be more interested in working out how to elicit the actual reasoning themselves. Whether that is triggering the hidden chain of thought, which is getting more hidden and harder to access — if anyone's seen the Anthropic stuff last week — or just getting it to reason in the chat, or on the page, or something like that. So that's how I would escape the argument, or try to avoid having to commit myself to saying that LLMs are always going to say something correct, or always going to be backing up their chain of thought with their answer. **Q1:** I guess just to build on your point and contribute to it: one push-back you could do is — whatever the system finds relevant, or what its mind finds relevant, might be different to what we find relevant, and that can be philosophically interesting itself, right? **Nick:** But yeah, I think it's really interesting. Thanks. --- ### Q2 — Adrian, on language acquisition and grounding **Chair:** We had a question from Adrian. **Adrian:** Can you hear me? **Nick:** I can hear you, but I can't see you. **Adrian:** Does this work? Can you hear me better now? **Nick:** Yes, perfectly. **Adrian:** Thanks so much for the stimulating talk — really enjoyed this. I just want to clarify exactly what your claim is. So is your claim that — there's a sense in which one might have the view that LLMs can't do philosophy because philosophy is partly an affective or phenomenological activity, but LLMs lack experience? So I would wonder what you think about language acquisition more generally. This might not be fully on point, so forgive me if it's a bit off — I just want to understand. Suppose I'm trying to learn Sanskrit. Sanskrit is not a language that is spoken orally by pretty much anyone nowadays, but it seems like I can learn Sanskrit without having any understanding of the exact phenomenology of Sanskrit speakers, or the things that maybe they were necessarily exposed to — I mean, maybe indirectly through the vocabulary of Sanskrit. I use Sanskrit as an example because it's so many thousands of years ago. So I'm trying to understand this case of the LLM in philosophy. In a sense, meta-semantically, the hyper-services that LLMs are kind of learning, with their classifiers and all these sorts of things, are in a sense grounded indirectly through humans that are training these things off the human text corpus, which itself is grounded in sense experiences. So an LLM says the word "dog" — "dog" is referring to dog in the same way I'm referring to dog, because I've experienced a dog, and I'm contributing indirectly to the training of the LLM. This is the same way that I can learn Sanskrit transitively, through a long causal history of people who previously were using Sanskrit and engaging with bodily things in ancient India — but I'm not directly experiencing ancient India. So I'm trying to understand why it matters to you so much that the LLM lacking experience has any necessary bearing on the authorship of philosophy texts. **Nick:** So I see some analogies — that was interesting — but I'm not quite sure of the question exactly. Because the argument I'm trying to make as regards the phenomenology was to try to say that we *might* expect LLMs to produce good phenomenology-based texts despite not having phenomenology themselves. **Adrian:** Oh, I see — so your view is that you can expect it to produce good philosophy texts despite not having — sorry, I misunderstood, exactly the converse of what you're saying. **Nick:** Sorry, that's almost certainly my fault. I beg your pardon. **Adrian:** No, no, that's probably my fault. Right. Okay, thank you. --- ### Q3 — Iraklis (?), on creativity **Chair:** Iraklis was next. **Q3:** Hello, hello. Hi — I hope you can hear me. I sort of wanted to ask you a little bit about the issue of creativity. One thing you might think about is — something that's [unclear] by [neighbours?] — they always say, you didn't say that much about it. It seems like it's all thought about some ideas. But anyway — I guess the name of how good a philosophy paper is, and how valuable it is, ties very closely to how creative it is. Creativity being something like departing from prominent patterns in the existing literature, or something like that. And then I guess the worry would be that LLMs per se — exactly what they do is reflect prompts. That is true, their output settings, and that's basically — exactly why you need human prompting, and that's where you say the sense of creativity is. Yeah. So I'm just interested if — what you think about that, something like that. **Nick:** Okay, good. Yeah, I think this is maybe the place to push as well. So what I would try to rely on here in terms of this creativity aspect — again, probably to accept that they are not creative in perhaps the way a person is. And yet — if you think about what I tried to argue in terms of the philosophical corpus acting as a filter on good arguments, on well-put-together arguments, and not only good uses of argumentative phrases and words, but also analyses of how these words and phrases should be used and things like that — the idea then, I guess what I would try to run together is: I would say, look, once you can statistically have vibes, sort of, of how to do philosophy well, how to make a good philosophy paper, of good philosophical arguments on the page — I guess as I speak, I want to say that that's giving you creativity for free. Because good uses of these words would be non-clichéd and non-repetitive — even if they're doing functions that these words have already done. And just one more thing about that — you know what I mean by the temperature setting on an LLM — the idea is the way you can make an LLM more creative, in one way, is you increase the chances of it choosing low-probability words, or lower-probability words than it would if it were in all the [default] settings. And that will force lower-probability words. But if you're still driving it with philosophical phrases, you might be able to ride this pseudo-creativity through temperature, using these rhetorical and argumentative explanation phrases. I think that's my answer. **Q3:** Yeah, great. Yeah, I always push this — what's creativity, anyway, and can we [capture] it by having varieties of [unclear]? Do you have any [unclear]? **Nick:** Okay, nice. Thank you. --- ### Q4 — on whether LLMs make new arguments, or just help philosophers **Chair:** A couple questions back over here. The microphone's getting turned around. Sorry. **Q4:** Hey, and thank you for your talk. If I have not misunderstood you — I think your thesis is that, because of [unclear], we should work with LLMs, because we could be more productive, or more creative, or more efficient, but with that — those LLMs do work, to create arguments from blank, or [unclear] by themselves, or anything else, can make up a new argument. So it's added — you can help. So this is my understanding of what you said — so maybe what you said is not that LLMs can create philosophical papers, like, themselves, but the thesis is actually that better philosophical papers could be produced by us. Is that right? **Nick:** Okay, good — at the end. Nice. I'm pretty sure I understood you — occasionally you're echoing — but if I'm getting anything wrong about what you asked me, just let me know. But I think I got it. I kind of did leave this open at the end. So when I talked about philosopher-prompters and thinking about how to prompt to get worthwhile philosophy out of these things — yeah, I guess I'd say, as of 2026, I think philosophers, if they want to read some worthwhile philosophy, should think about how they could prompt an LLM into producing that worthwhile philosophy. And then you could ask questions about who is the author of this text as well — you could say, well, was it the philosopher-prompter? Was it the LLM? I don't know what to say about that right now. What could potentially happen in the future, I guess, at least it seems a possibility to me, would be: as LLMs get more and more sophisticated, as long as the LLM knows that it's doing the analytic philosophy game and its job is to produce some worthwhile philosophy — rather than just a review or a brief summary — then maybe the necessity for philosopher-prompters will reduce and reduce and reduce, because easier and easier prompts will be able to get better and better responses. And then we might get to the *Hitchhiker's Guide to the Galaxy* place, which is: we ask the philosophical question, "what is the answer to life, the universe and everything?", and then we get the answer. But then of course we do have to worry about whether we will understand the answer, and what the question is in the first place. But this is super speculative, of course. **Q4 (follow-up):** A big follow-up. It's working now. [unclear] — where there is — the school stage is — how, biology, geography, the world, the past — is the time between the prompt and [unclear]. But it seems in this case, like certain Plato dialogues, in which there is a young Socrates answered, and then the other one gives some problems to Socrates, and Socrates replies. But it seems that the main contribution to the philosophical dialogue and consultant is not from the [students?] asking — by — even in [unclear] — and even if it's [unclear]. [Nick's response was not captured before the next question began.] --- ### Q5 — Bradley, on what exactly the key claim is **Chair:** Bradley's next. **Bradley:** Hello. Thanks for the talk. I had — I think I clear a paper — a question about just what exactly the key claim was. Is it that AI systems can produce sociological texts, or is it that AI systems can engage in the activity of philosophy? Because they're slightly different claims. I mean, they might do both, but — your answer to the first conserves the kind of aesthetic production. It is at this point that, like, philosophical text just sort of stands on its own and just history, and the way that art does — but then if that's it, AI can produce a lot worse, but only in like a purely productive or causal sense. It doesn't indicate they engaged in the process of doing philosophy to produce the text any more than, like, the text was assembled by, you know, typewriters, exactly. **Nick:** Yeah. I don't really want to say that LLMs are doing philosophy, or that a prompter is doing the philosophy with the LLM. I want to say that, despite it being a quite different process to producing the text, we have good reasons to think that that text can — if we prompt these things correctly — be worth reading. And just to double check — with "worth reading", all I mean by that is exactly what you'd mean for a human philosopher. --- ### Q6 — Maomi (?), on the definition of "worth reading" and paradigm shifts **Chair:** Maomi, what's next? **Q6:** Yes, my question relates to your previous voice. So I want to know more about the definition of "worth reading", because you have emphasised it several times. For example — there are a lot of philosophical papers published every day, in some good philosophy journals, but many of them are not worth reading, even if they got published. So I'm thinking — you said you are suggesting that they're going to publish a philosophical work that's worth reading, in the sense that they're going to publish something like some philosophical context that every common philosopher can do? Or some very, very — say something like, among the great philosophers, there's a possibility — say, for example, quality philosophers that, you know, change the paradigms of philosophy. Like, also I think Israel — a point about changing the paradigm: introducing new concepts, new ways, new patterns of thinking about things. So what's your exact claim about "worth reading"? **Nick:** Okay, thanks. Regarding the "worth reading" thing — I am going to be a little bit slippery about this. The reason I'm doing this is because I think we have a fairly good idea what this means. There are loads and loads of bad philosophy papers, of course — we don't publish them, other people publish them — but there are loads and loads of papers which are not worth reading. And what I'm trying to say is: we have good reason to think that an LLM can produce something that you might think, after reading it: huh — that was worth reading. That was an interesting argument. That was an interesting conclusion to draw. Or that was an observation which I've never thought of before — this sort of stuff. So that's all I mean by "worth reading". And I'm not at all saying that we should publish these things. I make no recommendations or anything like that. I am saying that — not even potentially — I think LLMs can produce things that are worth reading. And I guess therefore, if journals try to publish things which are worth reading, LLMs are creating publishable, or publication-worthy, texts. But I'm not saying they should be published, or anything like that. Finally, just about the paradigm-shift stuff — this comes back to what the other questioner asked about creativity. I guess I don't see any reason to think that if an LLM is trained well on a corpus, and uses its philosophical vocabulary well, there's no reason why it can't use that philosophical vocabulary to do paradigm shifts. *Punto.* --- ### Q7 — Andrea, on whether LLMs can referee or run journals **Chair:** All up over here. Andrea. **Andrea:** I screen, and I also referee papers. People always ask this. It's just interesting, but it's on people's minds. There's "can", and there's "should". Can you give a paper to an LLM and prompt it in such a way as it will say something philosophically interesting about the paper? And can it say something philosophically interesting as a referee on this paper? **Nick:** Yeah — I think you can probably get a pretty good referee's report with minimal prompting. Whether you should do this — and submit it to a journal without telling the journal that's what you've done — you certainly should not do that, of course. Because if it's the journal that's asked you to do the review, you are responsible for what you sent back. But if you're asking, is it capable of doing this — then yes, certainly. **Andrea:** Let me add a little bit to my question. Can a journal be run by an LLM judge — whether something is published? **Nick:** That's two questions then. The "can", I guess — again, if I want to stick to the courage of my convictions, and today I do — it should certainly be able to make good decisions and good analyses of articles written. It would depend on the prompt of course, and where it fits into a human's workflow. And should — yeah, I guess, why not? As long as the journal is honest about that's what's going on, then why not? And then you get this cool idea, that you can have journals entirely run, and publishing LLM-generated philosophy. That'd be fun. --- ### Q8 — David Harrison again, on responsibility, copyright and plagiarism **Chair:** Any final questions? **David:** Yeah. We're talking about responsibility. I guess, like, that's another question to ask, of course — my questions of like, authorship, like, with copyright and plagiarism and stuff like this, and like, where the something else is coming from. Like, I'm fine talking about LLMs contributing to philosophy in the abstract, but then, obviously, we just talked about responsibility, and talking about, you know, making judgements that impact people's careers. So then that question of authorship doesn't seem to be, like, a person-only contribution, sort of considerations. Used to be — is this, like, are is this like a derivatively plagiarising the corpus of philosophy and not really being able to use [unclear]? So that seems to inform the "should" question a little bit. I don't know. **Nick:** Good. On the copyright question — there's so much to ask about that, and the very last question as well. First of all, what I just said there is by no means an endorsement of how the big companies in the United States that make these models run. So I just want to make that particularly clear. There is maybe some hypocrisy that I use these systems so much — maybe I need to reflect on that a little bit more, to try and take away that issue, and quarantine myself against it at least a little bit. I would say, well, okay, I'm talking in the abstract about open-source LLMs, and all of the authors are being told and fairly compensated — which is maybe a cheat, but you can hear what I'm saying as a sort of with-that-qualification thing. And then just about — when you connected that to the responsibilities of decisions being made in journals and stuff like that — I guess, I don't know, maybe I need to think about this a bit harder, but it seems to be a slightly different question to the one about copyright. And right now — this is maybe not my worked-out opinion right now — I'd say: as long as everything is made clear to whoever is working with these systems, that it is a system making decisions, and this is everyone's free choice, then maybe — yeah, then I think that is probably okay. But that is not to say that we should replace all journal editors with LLMs, of course, or anything like that. --- ## Closing **Chair:** Okay, please join me in thanking our speaker. **Nick:** Thank you, everyone. Again, wish I could be there in person, but — yeah, hope you're enjoying yourselves, and thank you for the excellent questions, and thanks to the organisers as well. Ciao. --- *La domanda non era se le macchine possano pensare, ma se i loro testi possano valere la pena di essere letti.*