AI, be less ‘stereotypical’ : ChatGPT’s speech is conventional but never unique

Tantucci, Vittorio and Sparvoli, Cralotta (2025) AI, be less ‘stereotypical’ : ChatGPT’s speech is conventional but never unique. Intercultural Pragmatics, 22 (2). pp. 231-258. ISSN 1612-295X

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Abstract

Can AI reproduce human interaction? It can, but only stereotypically. While it can simulate (and even exaggerate) dialogic engagement, its lexicon is less diverse, and the speech acts it realizes are more repetitive and less varied (we took directives as an example). Most importantly, AI struggles to represent ‘conversational uniqueness’, that is ways to interact that define the specificity of a particular conversation and are not entirely conventional. We discovered this after analyzing dialogic resonance (the re-use of an interlocutor’s construction), recombinant creativity (the creative reformulation of an interlocutor’s construction), relevance acknowledgement (the acknowledgement of what an interlocutor said) and other variables from a sampled section of the CallHome Corpus of Chinese telephone conversations. After feeding ChatGPT with speakers’ demographics and contextual information, we asked it to reproduce telephone interactions among Chinese family members. We then fitted a conditional mixed effects Bayesian regression comparing the two datasets. We found that AI over-generalizes human dialogue. It provides a stereotypical way of conversing but shows scarce flexibility in including ‘atypical’ and unconventional utterances, which are, in turn, constitutive of human interactions that occur in real life.