If AI Outputs Aren’t Speech, Who Has to Prove They’re Human? | Lawfare
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A growing body of legal scholarship argues that large language model (LLM) outputs are not “speech” under the First Amendment and therefore may be regulated without the scrutiny ordinarily applied to restrictions on expression. Garcia v. Character Technologies, a wrongful-death suit brought after 14-year-old Sewell Setzer III died following months of conversations with an AI character, resulted in one of the first judicial opinions addressing the constitutional status of chatbot outputs. Ruling on the company’s motion to dismiss, U.S. District Judge Anne Conway wrote that she was “not prepared to hold that [LLM] output is speech” and allowed product liability and negligence claims to proceed. Garcia settled in January 2026, but other suits continue with similarly disturbing facts alleging that chatbot outputs played a role in medical crises, violence, or providing sexualized content to minors. Following these suits, a bevy of federal and state proposals would change whether and how people can receive information from chatbots.<br>Whether the no-speech position is doctrinally correct is one question. What it would take to administer that position is another. If human expression is protected but machine output is not, legal coverage may depend on whether a person created, selected, edited, or adopted—that is, knowingly put forward as one’s own—the words generated by the LLM.<br>Yet ordinary text rarely reveals whether it was written by a person, generated by a model, or produced through some combination of the two. If human attribution determines whether the First Amendment applies, the law needs both an attribution standard and a default when attribution cannot be established. Administering that rule would mean sorting human from machine expression at scale—a task no existing tool can reliably perform. The likeliest substitutes, identity and personhood verification, establish who a speaker is or that a speaker exists—not who authored a given text. Either approach burdens the very expression the rule purports to leave protected.<br>The burden of that uncertainty would likely fall more on users and readers than model developers. Enforcing a human-attribution rule across accounts, platforms, and disputed works requires some way to distinguish person from machine. Existing methods either cannot reliably distinguish between the two or demand more information about the speaker. The risks include reduced anonymity, greater surveillance, and pressure to use identity or personhood as a proxy for authorship. A consequentialist argument for excluding artificial intelligence (AI) output from First Amendment coverage should account for those costs when human involvement is mixed or disputed.<br>The No-Speech Position<br>The no-speech position argues that because no person stands behind a model’s words at the moment of generation, those words are not First Amendment-covered “speech.” The leading versions of the no-speech argument arrive at the same conclusion via different routes. Mackenzie Austin and Max Levy argue that machine output lacks “speech certainty:” No human speaker knows what a model will say as it says it. Peter Salib contends that AI output is the protected speech of no one—not the model, developer, or user. David Atkinson, Jena Hwang, and Jacob Morrison argue that frontier models lack communicative intent and therefore produce no speech at all.<br>The appeal is understandable. If model outputs are treated as speech, laws regulating them may trigger heightened First Amendment review. That result can seem perverse for laws intended to address product safety, fraud, or discrimination. The impulse is not frivolous: It reflects a genuine worry that ordinary First Amendment doctrine might otherwise give constitutional shelter to large areas of automated system behavior.<br>The approaches differ over when subsequent human interaction is enough to earn constitutional protection, but each makes human attribution the deciding factor.<br>Benjamin Wittes framed the doctrinal pressure from the other direction. Where some no-speech scholars deny protection to machine output to avoid an unpalatable result, he argued that existing doctrine, followed faithfully, already extends protection to it. Writing in Lawfare, he arrived at what he called “the first machines with First Amendment rights.” Machines don’t have constitutional rights, but a company’s expressive rights are not the machine’s; they are the rights of people who own and direct it. But a court need not give rights to a machine to recognize that...