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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - AI, be less ‘stereotypical’
T2 - ChatGPT’s speech is conventional but never unique
AU - Tantucci, Vittorio
AU - Sparvoli, Cralotta
PY - 2025/8/4
Y1 - 2025/8/4
N2 - 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.
AB - 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.
KW - AI
KW - Pragmatics
KW - computational linguistics
KW - alignment
KW - resonance
U2 - 10.1515/ip-2025-2003
DO - 10.1515/ip-2025-2003
M3 - Journal article
VL - 22
SP - 231
EP - 258
JO - Intercultural Pragmatics
JF - Intercultural Pragmatics
SN - 1612-295X
IS - 2
ER -