Authors: Z Ashktorab, A Buccella, J D'Cruz, Z Fowler, A Gill, KY Leung, PD Magnus, J Richards
Year: 2025
Published in: arXiv preprint arXiv:2507.02745, 2025•arxiv.org
Institution: IBM Research, University at Albany
Research Area: Human–AI interaction, AI systems evaluation, UX, User Experience
Discipline: Computer Science, Human–Computer Interaction (HCI)
In a preregistered study with 162 participants, people generally prefer explanatory apologies from LLM chatbots over rote or purely empathic ones—though in biased error scenarios empathic apologies are sometimes favored—highlighting the complexity of designing chatbot apologies that effectively repair trust.
DOI: https://doi.org/10.48550/arXiv.2507.02745
Citations: 1