More Isn't Always Better: Balancing Decision Accuracy and Conformity Pressures in Multi-AI Advice
Just as people improve decision-making by consulting diverse human advisors, they can now also consult with multiple AI systems. Prior work on group decision-making shows that advice aggregation creates pressure to conform, leading to overreliance. However, the conditions under which multi-AI consultation improves or undermines human decision-making remain unclear. We conducted experiments with three tasks in which participants received advice from panels of AIs. We varied panel size, within-panel consensus, and the human-likeness of presentation. Accuracy improved for small panels relative to a single AI; larger panels yielded no gains. The level of within-panel consensus affected partic...
| Authors | Yuta Tsuchiya, Yukino Baba |
|---|---|
| Primary category | cs.HC |
| Published | 23 March 2026 |
| Last updated at source | 23 March 2026 |
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