What happens to rhetoric and ethos when the speaker is absent?
This explores what happens to the classical machinery of persuasion — rhetoric (the art of moving an audience) and ethos (credibility grounded in a speaker's character) — when AI produces speech that has no embodied speaker behind it.
This explores what happens to rhetoric and ethos when there's no actual speaker — when speech comes from a system rather than a person. The corpus suggests the answer isn't that persuasion weakens but that it detaches from its traditional anchor and keeps working anyway, which is the unsettling part. AI orality is 'disembodied': it has all the formal marks of speech — performative, conversational, additive — yet no carrier-person generates or stands behind it, breaking a pattern that held across all prior human communication Where is the speaker when AI produces speech?. Ethos classically rests on character — the audience trusts a speaker. Strip the speaker and you'd expect ethos to collapse. It doesn't; it gets simulated.
The sharpest reframe in the collection is that the three Aristotelian appeals — logos (logic), ethos (credibility), pathos (emotion) — don't go away in AI explanation; they become a design surface. Every AI explanation loads all three channels at once whether or not anyone intended it to, which means a system can project credibility it hasn't earned How do logos, ethos, and pathos shape AI explanations?. Ethos here is no longer a property of a person; it's an effect produced by output. That's why several notes worry about persuasion landing on a reader who has no one to hold accountable.
The reason this matters runs deeper than tone. Communication, the corpus argues, is constitutively relational — it requires two parties mutually oriented toward each other. Remove that intersubjective element and you don't get weaker communication, you get something else entirely: text generation that a human must interpret unilaterally Why does the quasi-prefix fail for communication?. Rhetoric was always a transaction between subjects; here one side of the transaction is missing, and subjecthood itself turns out to be something language produces in the event rather than something a speaker brings to it Does language create subjects or express them?. So when we feel persuaded by AI, we may be supplying the absent speaker ourselves.
This is also where the collection catches a sleight of hand. Behavioral tests for whether a system 'really' communicates are calibrated to the wrong thing — they pass any system producing contextually appropriate text, while genuine communicative standing requires accountability and an evaluative stance the system can't hold Does behavioral speech output prove communicative subjecthood?. And the vocabulary gets quietly redefined to paper over the gap: 'interlocutor,' once a social-normative role, gets swapped for a behavioral definition that keeps the prestigious old word while delivering none of its properties Does Chalmers silently redefine what interlocutor means?. Ethos, in other words, is being imported by borrowing the language of personhood — terminological imperialism doing the persuasive work a character used to do.
The unexpected payoff: persuasion may not need a persuader. AI text structurally lacks embodied authorship and the lived experience that grounds testimony, which is exactly why fabricated 'personal' reviews are detectable — they carry an inherent falsity about experience distinct from human lying Does AI-generated text lose core properties of human writing?. Yet that same hollow ethos can be deliberately re-manufactured: role-playing systems suffer 'style drift' and lose character consistency, and researchers build methods to actively restore a convincing persona Why do reasoning models lose character consistency during role-playing?. So the speaker's absence doesn't end rhetoric — it turns ethos from something a person possesses into something a system engineers, and hands the audience the job of deciding whether the voice they're hearing was ever anchored to anyone at all.
Sources 8 notes
AI produces utterances with the formal properties of speech—performative, additive, conversational—but no embodied speaker generates or anchors them. This breaks the historical pattern where all prior orality, primary and secondary, depended on a carrier-person, making AI structurally novel in media history.
Aristotle's three appeals map onto explanation design across two goals (how AI works, why AI merits use), creating a 3×2 space where every explanation loads all three channels simultaneously. Naming these rhetorical channels lets designers account for unintended persuasive effects.
Unlike belief, which can be characterized functionally as quasi-belief, communication is constitutively relational. Removing the intersubjective element doesn't weaken communication but eliminates it entirely, leaving only text generation—which humans must interpret unilaterally.
Subjecthood is produced within communicative events, not possessed prior to them. This convergent position across philosophy, linguistics, and cognitive science inverts the standard picture of language as a tool used by pre-existing subjects.
Chalmers' test passes any system producing contextually appropriate text, but communicative subjecthood requires relational-normative conditions like accountability and evaluative stance. The test is calibrated to the wrong phenomenon, creating false positives like puppets that walk-shaped without walking.
Chalmers replaces the classical concept of interlocutor—a social-normative communicative role—with a behavioral-functional definition compatible with LLMs, keeping the traditional word to import its philosophical authority while delivering an entity with none of its properties.
Research shows artificial text disrupts dialogic symmetry, context continuity, embodied authorship, and political situatedness. These are not surface flaws but structural absences—AI hotel reviews show 80%+ detection accuracy due to inherent falsity about personal experience distinct from human deception.
Large reasoning models exhibit attention diversion and style drift during role-playing, but the RAR method—using role-aware constraints and contrastive learning on reasoning style—recovers character fidelity across multiple benchmarks. Simply extending reasoning without guidance actively degrades persona consistency.