Work

Does More Advice Help? The Effects of Second Opinions in AI-Assisted Decision Making

Year: 2024

Type: article

Abstract: 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.

Source: Proceedings of the ACM on Human-Computer Interaction

DOI: 10.1145/3653708

Authors: Zhuoran Lu, Dakuo Wang, Ming Yin

Institutions: Purdue University West Lafayette, Northeastern University

Language: English

Topic: Human-Automation Interaction and Safety

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

Open Access status: hybrid

Funder: Universitas Brawijaya

Award: G2355114002