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

Zhuoran Lu, Dakuo Wang, Ming Yin
1/13/2024
cs.HCcs.AI

No confident code implementation found for this paper. 3 possible matches can be shown below.

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 3 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{lu2024does,
  title  = {Does More Advice Help? The Effects of Second Opinions in AI-Assisted Decision Making},
  author = {Zhuoran Lu and Dakuo Wang and Ming Yin},
  year   = {2024},
  eprint = {2401.07058},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2401.07058v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2401.07058.svg)](https://codeofpaper.com/paper/2401.07058)

Discussion