2024/01/13 by Zhuoran Lu, Lu, Zhuoran, Dakuo Wang +3 · 1 citation
Decision Sciences · #Artificial Intelligence (cs.AI) #Decision-Making and Behavioral Economics #FOS: Computer and information sciences #Forecasting Techniques and Applications #Human-Computer Interaction (cs.HC) #Impact of AI and Big Data on Business and Society
paper · pdf · doi:10.48550/arxiv.2401.07058
openalex publication_date 2024/01/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
AI assistance in decision-making has become popular, yet people's inappropriate reliance on AI often leads to unsatisfactory human-AI collaboration performance. In this paper, through three pre-registered, randomized human subject experiments, we explore whether and how the provision of second opinions may affect decision-makers' behavior and performance in AI-assisted decision-making. We find that if both the AI model's decision recommendation and a second opinion are always presented together, decision-makers reduce their over-reliance on AI while increase their under-reliance on AI, regardless whether the second opinion is generated by a peer or another AI model. However, if decision-makers have the control to decide when to solicit a peer's second opinion, we find that their active solicitations of second opinions have the potential to mitigate over-reliance on AI without inducing increased under-reliance in some cases. We conclude by discussing the implications of our findings for promoting effective human-AI collaborations in decision-making.