Mind, Matter, and Meaning

A well-trained language model produces a sentence about a maple tree. The sentence parses, predicts, and pleases. Did the model say something about a maple tree?

A growing line of argument answers yes — not by claiming the model has thoughts, perceives leaves, or means anything in the rich, mental sense, but by claiming something cleverer. The model’s outputs, the argument goes, inherit their meaning the way a counterfeit twenty inherits the design of a real twenty: by lineage. The tokens belong to a public linguistic practice with its own teleology. They have been selected, refined, and stabilized through generations of human speakers using “maple” to talk about maples. When an LLM emits the word, it produces a token of a type whose proper function — in Millikan’s sense — already exists. The model does not need to mean anything mentally. The word does the meaning for it. Call this the borrowed-meaning move.

It is a serious argument. Jumbly Grindrod’s “Large Language Models and Linguistic Intentionality” works from Gareth Evans on naming practices and Ruth Millikan on teleosemantics, and one cannot wave the view off by pointing out, again, that the model lacks consciousness.¹ Grindrod has agreed the model lacks consciousness. He has carved out a space — linguistic intentionality — that allegedly does not require any mind on the speaker’s end at all. The thought is bracing: meaning, in the public sense, lives in the practice, and any device that successfully participates in the practice is meaning-bearing whether or not anyone is home.

The view deserves the strongest version one can give it. Words really do have public lives. “Water” refers to H₂O whether the speaker can recite the formula or not; a sneeze that sounds like “achoo” does not refer, but a careful utterance of “achoo” in a Burns Night recitation might; lineage matters. Millikan built her account precisely to capture this: a token gets its content from the cooperative history that selected it.² Producers and consumers, refined over generations, settle what a sign is for. So far, so good.

The trouble starts when the LLM walks into the cooperative history and asks for a seat at the table.

Millikan’s mechanism has two halves, and the borrowed-meaning move quietly drops one. Producers make signs; consumers take them up; selection happens because consumers’ uptake feeds back into which producer-tokens persist.³ A bee that waggles in the wrong direction starves the hive; a hive that ignores good waggles starves itself. Selection requires that the loop close — that getting it right about the world makes the difference between thriving and not. Strip out the loop and you have not teleosemantics; you have stenography with extra steps.

Now the LLM. What does it select for? It selects for tokens that look, statistically, like the tokens that came before them. The objective function rewards plausibility under a distribution, not correctness about maples. The model’s “consumers” — its loss function, its trainers, its users — do not punish it when its outputs misrepresent maples; they punish it when its outputs read poorly. There is a feedback loop, but the loop runs through human readability, not through the world. When humans read fluently, the model is reinforced; when humans wince, it is corrected. The maple has no vote.

This matters because the proper function Grindrod wants to inherit was forged in a different kind of loop. The word “maple” stabilized in human speech because, over generations, calling maples maples helped people find sap, identify wood, build sugar shacks, and not eat the wrong leaves. The lineage runs through successful engagement with maples. When a contemporary speaker uses the word and gets things right or wrong, she is the latest carrier of that lineage because her uses, too, are accountable to maples. The line of descent is not just morphological; it is causal-ecological.⁴

The LLM joins the morphology and skips the ecology. Its tokens are the right shape, but the path by which they arrived bypasses the maples entirely. To insist that they nonetheless inherit maple-content is to confuse the costume with the role. A child wearing a postman’s uniform delivers nothing.

One can almost hear the rebuttal forming: surely the model’s training data was itself produced by speakers whose words were maple-accountable, and so the lineage runs through the model’s outputs after all. This is the move that makes the argument feel airtight, and it deserves to be taken seriously. But notice what it requires. It requires that being trained on tokens produced by maple-accountable speakers counts as participating in the maple-accountable lineage. By that standard, my photocopier participates too, and so does the optical scanner that produced the JPEG of someone else’s botany textbook. If the criterion for inheritance is “your outputs causally trace back to outputs produced by accountable speakers,” it sweeps in every device that traffics in linguistic shapes. We have not extended teleosemantics; we have diluted it into ink-on-paper.

A sharper friend of the view will press here, because the diagnosis so far leans on the producer side and Millikan’s deeper innovation was the consumer side. So grant it: maybe the model is no producer worth the name, but its human users surely are consumers — they take up its tokens, act on them, and feed their satisfaction or dismay back into the next round of training. Doesn’t that close the loop after all, with us standing in as the consumers Millikan requires? It is the best version of the objection, and it almost works. What it leaves out is what the consumers are selecting for. A Millikanian consumer closes a loop only when its uptake tracks whether the sign got the world right; the hoverfly’s visual system is a consumer of the bee-dance only because hoverflies that misread the dance leave fewer offspring. The human reading an LLM’s paragraph is selecting for whether the paragraph reads well, coheres, flatters the prompt — and a fluent falsehood passes that filter as smoothly as a fluent truth. The consumer is real; the kind of selection is wrong. We are consumers of the model’s prose the way we are consumers of a pleasant melody, not the way the hive is a consumer of the waggle. The loop closes on us, and stops there, well short of the maple.⁵

The serious version of the argument has to add something: that the LLM does not merely repeat tokens but produces new tokens whose proper function is settled by the practice. Fine. But the proper function of “maple” — the thing the lineage selected for — was the function of being deployed in maple-accountable ways. A producer that emits “maple” without any sensitivity to whether maples are present is, in Millikan’s own terms, not performing the function. It is doing something function-shaped. Grindrod knows this; he concedes that Millikan herself would resist his application.⁶ That concession is the ballgame. The framework was built around a kind of accountability the LLM does not have, and once you remove the accountability, the inheritance has nothing to inherit.

There is a softer version of the borrowed-meaning move that survives all this and is worth keeping. LLM outputs are not meaningless noises; they are parasitic on meaning. They function as inscriptions — like the words in a book lying open on a desk. The book is full of meaning in the sense that meaning runs through it: the author meant things, and a competent reader will recover them. We do not therefore conclude that the book is a meaner. The book is a vehicle. So is the model.

Calling the model a meaner because its outputs traffic in meaningful tokens is the same kind of category mistake as calling a perfectly transcribed prayer a worshipper. The transcription preserves the words; the worshipper supplies the world-directedness; the difference, in our tradition, is the whole point.⁷ Strip it away and you have not democratized intentionality. You have just mislaid it.

What is left, then, of the model’s apparent eloquence? Quite a lot, actually — and this is where the gentlemanly part of the knife fight ends in a handshake. I use these tools. I find them genuinely useful. LLMs are extraordinary engines of linguistic regularity. They surface patterns in our practices that we ourselves had not articulated. They are useful in the way a very good concordance is useful, except they generate as well as retrieve. Treating them as oracles dishonors them; treating them as colleagues misclassifies them; treating them as new instruments of inquiry treats them right.

Borrowed meaning is still borrowed. The maple still does the work. And anyone who writes the word — child, philosopher, model, footnote-machine — only joins the practice by doing what the practice was always for: getting things right about the world, or being corrected when one fails. The model does not fail in that way, because it cannot. It does not succeed in that way either. It produces the shape of success, which is a real and beautiful thing, and which our language has a perfectly good word for.

We call it style.

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Notes

1. Jumbly Grindrod, “Large Language Models and Linguistic Intentionality,” Synthese 204:71 (2024). Grindrod’s strategy is to grant the cognitive emptiness of LLMs and recover meaning at a different level: the linguistic practice itself. Drawing on Gareth Evans’s distinction between producers and consumers of a naming practice (Evans, The Varieties of Reference, ed. John McDowell [Oxford: Clarendon, 1982], ch. 11), and on Millikan’s teleosemantic account of conventional signs, Grindrod argues that an LLM can stand in the consumer role even though it lacks the demonstrative-recognitional capacities Evans required of producers. The argument is the strongest version of the LLM-meaning move currently in print; the response developed here grants the structure and contests the inheritance step. ↩
2. Ruth Garrett Millikan, Language, Thought, and Other Biological Categories: New Foundations for Realism (Cambridge, MA: MIT Press, 1984), chs. 1–2; and “Biosemantics,” Journal of Philosophy 86 (1989): 281–297. Millikan’s “proper function” is the function a trait has in virtue of the evolutionary or learning history that selected for its predecessors. Applied to signs, the proper function of a token-type is what its ancestors did that made it persist. The water-as-H₂O case is most directly developed in Hilary Putnam, “The Meaning of ‘Meaning,’” in Mind, Language and Reality: Philosophical Papers, Volume 2 (Cambridge: Cambridge University Press, 1975), 215–271; the convergence between Putnam’s causal-historical externalism and Millikan’s teleosemantics is one of the more underappreciated agreements in twentieth-century semantics. ↩
3. The producer-consumer asymmetry is central to Millikan’s account and is what distinguishes teleosemantics from mere informational semantics à la Dretske (Knowledge and the Flow of Information [Cambridge, MA: MIT Press, 1981]). Information by itself does not generate the normative dimension — the difference between succeeding and failing at representation — because mere correlation between sign and signified does not yet involve the kind of cooperative history that lets a sign be wrong. The bee-dance example is Millikan’s own (Language, Thought, and Other Biological Categories, 96–98); the philosophical point is that proper function lives downstream of consumer uptake, not in the producer’s intrinsic states. Peter Godfrey-Smith, “Mental Representation, Naturalism, and Teleosemantics,” in Teleosemantics: New Philosophical Essays, ed. Graham MacDonald and David Papineau (Oxford: Oxford University Press, 2006), 42–68, provides the cleanest critical overview. ↩
4. The morphology/ecology distinction sharpens an old worry. Stevan Harnad’s symbol-grounding problem (Harnad, “The Symbol Grounding Problem,” Physica D 42 [1990]: 335–346; and “Symbol Grounding and the Origin of Language,” in Computationalism: New Directions, ed. Matthias Scheutz [Cambridge, MA: MIT Press, 2002], 143–158) holds that the meaning of a formal symbol system cannot be fixed by relations among symbols alone, on pain of regress — the symbols must be grounded in a non-symbolic capacity to sort, label, and interact with what they denote. Harnad’s vivid gloss is that language lets us “steal” categories by hearsay rather than “earn” them through sensorimotor “toil,” but the theft presupposes that some categories were earned the hard way: “it cannot be linguistic theft all the way down” (2002, abstract). The borrowed-meaning move is precisely an attempt to make it theft all the way down — to let the LLM inherit grounded content without any grounding of its own. Teleosemantics is supposed to be the framework that explains how grounding gets transmitted across a lineage; the present objection is that transmission, in Millikan’s sense, requires the consumer’s uptake to remain world-accountable, which is exactly the link the LLM’s training loop severs. The ecology is the grounding; the morphology is the theft. ↩
5. The consumer-side reply is the strongest objection to the argument, since it grants the producer-side point and relocates the loop in human users. The reply fails because Millikanian consumption is not mere uptake but selection-relevant uptake: the consumer’s responses must covary with the sign’s worldly accuracy in a way that differentially preserves accurate producer-tokens. This is the feature that, on Godfrey-Smith’s reading, distinguishes a genuine teleosemantic feedback process from a merely causal one — see Peter Godfrey-Smith, “Mental Representation, Naturalism, and Teleosemantics,” in Teleosemantics: New Philosophical Essays, ed. Graham MacDonald and David Papineau (Oxford: Oxford University Press, 2006), 42–68, esp. the discussion of which feedback loops Millikan’s biological cases license. Human satisfaction with an LLM paragraph covaries with fluency, coherence, and prompt-fit, not with the paragraph’s accuracy about its ostensible subject — fluent falsehood and fluent truth pass the same filter. The point parallels the standard charge against pure informational semantics (Dretske, Knowledge and the Flow of Information [Cambridge, MA: MIT Press, 1981]): correlation alone yields no norm of correctness, because a sign that merely tracks what its consumers reward cannot thereby be wrong about the world. The LLM’s consumers reward readability; readability is not a world-tracking norm; so the loop, though real, is the wrong kind of loop. ↩
6. Grindrod, “Large Language Models and Linguistic Intentionality,” §4. The concession that Millikan would resist his application is doing more work than Grindrod treats it as doing. Millikan’s framework is not merely a name-tag for “tokens have public meanings”; it is a specific account of what makes a token-type have a meaning, and the answer is that consumers’ uptake of the token, in selection-relevant feedback loops, shapes which producer-tokens persist. Strip out the consumer side of the loop — which is exactly what the LLM case does — and the framework no longer applies. The response in the main text follows the line developed in Millikan, “What Has Natural Information to Do with Intentional Representation?” Royal Institute of Philosophy Supplement 49 (2001): 105–125. For a sympathetic but firm rebuttal of LLM teleosemantic inheritance from a different angle, see Marek Havlík, “Meaning and Understanding in Large Language Models,” Synthese 203:113 (2024). ↩
7. The vehicle/content distinction at work here echoes Tim Crane’s deployment of it in “Is There a Perceptual Relation?”, in Perceptual Experience, ed. Tamar Szabó Gendler and John Hawthorne (Oxford: Oxford University Press, 2006), 126–146, and connects to the Chinese Room’s underlying point in Searle, “Minds, Brains, and Programs,” Behavioral and Brain Sciences 3 (1980): 417–424 — that formal manipulation of meaningful tokens is not itself a meaning-bearing activity. The prayer-transcription analogy is mine; the structural point — that a vehicle which carries meaning does not thereby produce meaning — is widely shared across the realist tradition the book sits within. Ch. 9 develops the Searlean version of the diagnosis at length. ↩