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arxiv: 2606.02973 · v1 · pith:24SCXZXXnew · submitted 2026-06-02 · 💻 cs.CL

Chatbots Output Meaningful (but Problematic) Language

Matthew Stone , Una Stojni\'c This is my paper

Pith reviewed 2026-06-28 11:10 UTC · model grok-4.3

classification 💻 cs.CL
keywords chatbotsmeaningLLMsphilosophy of languageintentionalismAI textsemantics
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The pith

Chatbot outputs have their ordinary meaning under standard theories of human language without needing to assume any mental states in the machines.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper sets out to show that AI chatbots produce meaningful language using the same theories that apply to human speech. This is because meaning does not depend on the producer having specific intentions or mental states that match the output. Humans sometimes say things that differ from what they have in mind, yet the language still means what it says. Therefore, chatbots do not require special new theories of language. This approach changes how we should think about and critique both human and AI-generated text without assuming the AI is conscious or rational.

Core claim

Utterances by AI chatbots are meaningful because a proper theory of human language already applies as is to current chatbots. Meaning is a low bar that does not require positing mental states, intentions, rationality, or other anthropomorphic assumptions in LLMs, since even in humans language production can depart from what the speaker has in mind.

What carries the argument

The principle that language production can depart from the producer's mental states or intentions while still carrying ordinary meaning.

If this is right

  • Answers from chatbots can express true propositions in the standard way.
  • Analyses of human language must handle cases where output does not match the speaker's intentions.
  • Engagement with chatbot text should treat questions of meaning separately from questions of whether the content is endorsed or the technology is useful.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Questions about whether chatbots 'understand' or 'intend' their outputs may not affect whether their sentences have meaning or truth value.
  • The same logic might extend to other systems that generate language without internal mental states, such as rule-based systems or animals.
  • Further work could examine specific cases of human language use where intentions and output diverge to see if the account holds.

Load-bearing premise

That language can be produced in ways that depart from the producer's mental states or intentions, as occurs in humans, and that this does not prevent the output from having ordinary meaning.

What would settle it

Evidence that meaningful language use always requires the producer's intentions to match the output, with no counterexamples in human communication.

read the original abstract

Are utterances by AI chatbots meaningful? Concretely, if a user asks, say, Anthropic's agent Claude, "What is the capital of Spain?" and Claude answers, "Madrid is the capital of Spain," does that sentence have its ordinary meaning -- and does it express a true proposition? Most ordinary users, as well as AI engineers, take the answer to be trivially "yes." However, many cognitive scientists, linguists, and philosophers of language argue that dominant intentionalist accounts of language and meaning deliver the opposite conclusion. Theorists more sympathetic to ordinary users' intuitions have therefore advocated a radical "de-anthropomorphization" of language, revising our understanding of mental states, intentions, and semantic content to capture the intuition that the outputs of LLMs are meaningful. We take a different approach. While we, too, argue that LLM outputs are meaningful, we contend that a proper theory of human language already applies, as is, to current chatbots. Meaning is a low bar: claiming that LLM outputs are meaningful does not require positing mental states, intentions, rationality, or the cognitive capacities requisite for communication in LLMs -- or, indeed, making any other anthropomorphic assumptions. People do have communicative intentions (typically successful ones), but nevertheless, even in humans, language production can depart from what the speaker has in mind. Our view has important consequences for how we should theorize about -- and critically engage with -- both human linguistic output and synthetically generated text. In particular, to say that chatbots produce meaningful text is not by any means to endorse what they output, or to assume that the technology is (or is not) good, powerful, appropriate, or useful.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper claims that utterances by current AI chatbots have ordinary meaning under existing theories of human language, without any need to posit mental states, intentions, or cognitive capacities in the chatbots themselves. It contrasts this conservative position with intentionalist accounts (which would deny meaning to LLMs) and with revisionary 'de-anthropomorphizing' approaches, arguing that the detachability of meaning from producer psychology is already licensed by cases in which human language production departs from what the speaker has in mind.

Significance. If the central argument holds, the result supplies a non-revisionary route to attributing truth-conditional content to LLM outputs, thereby simplifying debates in the philosophy of language and AI ethics: meaning can be ascribed (and outputs can be criticized) without anthropomorphic assumptions or endorsement of the technology. The manuscript correctly notes that meaning attribution is independent of whether the technology is 'good' or 'useful.'

major comments (2)
  1. [§1] §1 (paragraph beginning 'Theorists more sympathetic...'): The claim that 'a proper theory of human language already applies, as is' is load-bearing, yet the manuscript does not identify or defend any specific non-intentionalist theory (e.g., a particular use-based, conventionalist, or truth-conditional account) that treats meaning as fully detachable from all producer psychology. Without this, the extension from human mismatch cases to the zero-psychology LLM case remains unsupported.
  2. [Introduction] Discussion of intentionalist accounts (early paragraphs of the introduction): The assertion that 'dominant intentionalist accounts of language and meaning deliver the opposite conclusion' is central to motivating the position, but no specific intentionalist theory is cited or shown to fail for LLMs while surviving the human mismatch cases; this leaves the contrast with the paper's own view unanchored.
minor comments (2)
  1. [Abstract] Abstract: The final sentence on consequences for 'theorizing about both human linguistic output and synthetically generated text' is stated at a high level of generality; a single concrete illustration of how the view alters analysis of one chatbot exchange would improve clarity.
  2. [Conclusion] The manuscript would benefit from an explicit statement of the scope (current LLMs only, or future systems as well) to avoid ambiguity about whether the argument is intended to be timeless.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for these incisive comments, which correctly identify places where greater specificity would strengthen the manuscript. We address each point below and will revise accordingly.

read point-by-point responses

  1. Referee: [§1] §1 (paragraph beginning 'Theorists more sympathetic...'): The claim that 'a proper theory of human language already applies, as is' is load-bearing, yet the manuscript does not identify or defend any specific non-intentionalist theory (e.g., a particular use-based, conventionalist, or truth-conditional account) that treats meaning as fully detachable from all producer psychology. Without this, the extension from human mismatch cases to the zero-psychology LLM case remains unsupported.

    Authors: We accept the referee's observation. The manuscript's core strategy is to remain theory-neutral and rely on the fact that detachability of meaning from producer psychology is already licensed by standard treatments of human cases; we therefore conclude that no revisionary move is required for LLMs. Nevertheless, the referee is right that the load-bearing claim would be more robust if concrete examples were supplied. In the revised version we will expand the relevant paragraph in §1 to name and briefly characterize two families of non-intentionalist views—conventionalist accounts (e.g., Lewis) and use-based approaches (e.g., later Wittgenstein and certain truth-conditional theories that locate meaning in public practice rather than individual states)—and show how each already accommodates human mismatch cases. This addition will make the extension to LLMs explicit without altering the paper's conservative stance. revision: yes

  2. Referee: [Introduction] Discussion of intentionalist accounts (early paragraphs of the introduction): The assertion that 'dominant intentionalist accounts of language and meaning deliver the opposite conclusion' is central to motivating the position, but no specific intentionalist theory is cited or shown to fail for LLMs while surviving the human mismatch cases; this leaves the contrast with the paper's own view unanchored.

    Authors: We agree that the contrast would be sharper with explicit references. The manuscript's claim is that, on any view requiring producer intentions or mental states for meaning, LLMs would lack meaning, while the human mismatch cases already show that such views must allow meaning to diverge from actual psychology. To anchor this, the revised introduction will cite representative intentionalist theories (Gricean and neo-Gricean accounts) and briefly note how each would treat the human cases versus the LLM case. This will clarify the motivation without committing the paper to any particular intentionalist framework. revision: yes

Circularity Check

0 steps flagged

No circularity: purely conceptual reinterpretation of independent linguistic theories

full rationale

The paper advances a philosophical position that standard theories of meaning already cover LLM outputs because human language production can already diverge from speaker intentions. This is presented as an application of existing accounts rather than a derivation that reduces to self-definition, fitted parameters, or a self-citation chain. No equations, data-fitting steps, or load-bearing uniqueness theorems appear; the argument rests on reinterpretation of ordinary human cases and does not construct its conclusion by renaming or smuggling in its own premises. The derivation is therefore self-contained against external benchmarks in philosophy of language.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The paper's position rests on assumptions about the nature of linguistic meaning drawn from philosophy of language, without introducing new entities or fitted parameters.

axioms (2)
  • domain assumption Meaning does not require the speaker to have corresponding intentions or mental states.
    This allows the theory to apply to LLMs and explains human cases where output departs from mind.
  • domain assumption Ordinary meaning attribution to utterances is independent of the producer's cognitive capacities for communication.
    Core to the 'low bar' for meaning in both human and synthetic text.

pith-pipeline@v0.9.1-grok · 5841 in / 1254 out tokens · 36327 ms · 2026-06-28T11:10:00.329739+00:00 · methodology

discussion (0)

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