"Sorry, it was my fault": Repairing trust in human-robot interactions. Issue 175 (July 2023) - Zhang, Xinyi; Lee, Sun Kyong; Kim, Whani; Hahn, Sowon
Highlights: Different types of competence-based failures do not impact trust differently on a significant level. Semantic and syntax failures are perceived as competence-based trust violations. Internal-attribution apology outperforms denial but not external-attribution apology. Denial is more harmful than no repair attempts for competence-based trust violations. Abstract: The current study develops a three-fold categorization (i.e., logic, semantic, and syntax failures) for technical failures that are commonly observed in human-robot interactions (HRI), and investigates it along with four trust repair strategies: internal-attribution apology, external-attribution apology, denial, and no repair. The 743 observations conducted through an online experiment reveal some nuances in participants' perceprions of competence- and integrity-based trust violations, which may reflect ontological differences between humans and machines. The analysis also shows significant main effects of failure types and repair methods on HRI-based trust.