Authors: M Riveiro, S Thill
Year: 2025
Published in: Proceedings of the 30th ACM Conference on User ..., 2022 - dl.acm.org
Institution: Linköping University, University of Skövde
Research Area: Explainable AI (XAI), Human-Computer Interaction
Discipline: Human-Computer Interaction
Users prefer factual explanations when AI outputs match expectations and mechanistic explanations when outputs deviate, with preferences influenced by response format (multiple-choice vs free text).
Methods: Participants were presented with scenarios involving an automated text classifier and asked to express their preference for explanations either through multiple-choice or free text responses.
Key Findings: User-desired content of AI explanations based on whether system behaviour aligns or deviates from expectations.
DOI: 10.1145/3503252.3531306
Citations: 30
