Authors: J Beck, S Eckman, C Kern, F Kreuter
Year: 2025
Published in: arXiv preprint arXiv:2509.08514, 2025 - arxiv.org
Institution: National Institutes of Health, National Center for Biotechnology Information
Research Area: Human-Computer Interaction (HCI)
Discipline: Human-Computer Interaction (HCI)
Human attitudes toward AI strongly influence performance in collaborative tasks, with skeptics showing better error detection and accuracy, while automation favorability increases overreliance on AI suggestions.
Methods: Randomized experiment with a controlled annotation task manipulating AI suggestion quality, task burden, and performance-based financial incentives; collected demographic, attitudinal, and behavioral data.
Key Findings: Impact of AI suggestion quality, task burden, and financial incentives on participant performance metrics (accuracy, correction activity, overcorrection, undercorrection); influence of demographic and psychological characteristics on performance.
Citations: 4
Sample Size: 2784