Against speech liberalism for generative AI

Abstract

Abstract Speech liberalism holds that the linguistic output of generative AI is continuous with human speech and should therefore be treated as meaningful in broadly the same way. Strong versions of this view take the fluent behaviour of chatbots to justify attributing genuine linguistic and cognitive agency, while nevertheless advocating caution when questions of moral or legal responsibility arise. I argue that this gives too much evidential weight to successful conversational interaction, where speaker intentions largely recede into the background. Once AI-generated speech contributes to serious harm, however, those intentions become central. More broadly, the paper challenges a way of theorising about AI speech that builds classifications of linguistic agency primarily from successful conversational interaction. I develop two independent but complementary arguments. The first is ethical–legal. I argue that classifying chatbot output as speech is not normatively neutral: within existing free-speech doctrine, it risks generating responsibility and liability gaps in cases of AI-mediated harm. The second is epistemic. I argue that the behavioural evidence supporting strong speech liberalism is systematically distorted by anthropomorphic bias, reinforced by AI design practices. The paper concludes that theories of AI speech should not be built exclusively from successful conversational exchanges and that, until a broader evidential case is made, a more conservative approach to AI speech is warranted in high-stakes contexts.