Authors: P Cooper, A Lim, J Irons, M McGrath, H Jarvis
Year: 2025
Published in: Proceedings of the ..., 2025 - dl.acm.org
Institution: Microsoft Research, Massachusetts Institute of Technology, University of Washington
Research Area: Human-AI Interaction, Trust in AI
Discipline: Human-Computer Interaction (HCI)
Trust in AI dynamically influences users' reliance on AI advice during a deepfake detection task, with no significant impact observed from the timing of AI advice delivery.
Methods: Researchers conducted an online study with participants performing a deepfake detection task, comparing performance across conditions where AI advice was provided either concurrently with decisions or after an initial evaluation. Computational modeling was used to analyze trust dynamics.
Key Findings: Impact of AI advice and its timing on task performance, and the dynamic role of user trust in AI based on expectations of its ability.
DOI: https://dl.acm.org/doi/10.1145/3706599.3719870
Citations: 1