Does More Advice Help? The Effects of Second Opinions in AI-Assisted Decision Making
This addresses the problem of ineffective human-AI collaboration due to over-reliance on AI, with incremental insights for decision-makers in AI-assisted settings.
The study investigated whether providing second opinions reduces inappropriate reliance on AI in decision-making, finding that always presenting a second opinion reduces over-reliance but increases under-reliance, while allowing users to solicit opinions can mitigate over-reliance without increasing under-reliance in some cases.
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.