When AI shows its rationale: user-visible rationale styles and the adoption of AI-mediated relational correction

Li, Zhenming, Jin, Ziyu, You, Shuchao, Li, Ting and Tse, Ying Kei (Mike) ORCID: https://orcid.org/0000-0001-6174-0326 2026. When AI shows its rationale: user-visible rationale styles and the adoption of AI-mediated relational correction. International Journal of Human-Computer Interaction Item availability restricted.

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Abstract

Generative AI is increasingly used to support interpersonal communication, yet little is known about how user-visible rationales shape users’ evaluations of AI-assisted messages. We examine this question in Chinese family group chats, where correcting older relatives’ health misinformation requires factual accuracy alongside care, respect, and face management. In a between-subjects experiment (N = 279), participants viewed the same corrective reply preceded by no visible rationale, a procedural rationale, or a relational rationale. Both rationale conditions increased performance expectancy, effort expectancy, and adoption intention while reducing AI-mediated authenticity concern. Relational rationale produced the largest reduction in authenticity concern, and its effect on performance expectancy strengthened as affective load increased. Overall, user-visible rationales appear to function as communicative frames that shape how users evaluate AI-assisted interpersonal messages, extending research on explainable AI and AI-mediated communication.

Item Type:	Article
Status:	In Press
Schools:	Schools > Business (Including Economics)
Publisher:	Taylor and Francis Group
ISSN:	1044-7318
Date of First Compliant Deposit:	1 November 2026
Date of Acceptance:	23 October 2026
Last Modified:	02 Nov 2026 14:30
URI:	https://orca.cardiff.ac.uk/id/eprint/190560

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