Biased AI improves human decision-making but reduces trust
Abstract
Current AI systems minimize risk by enforcing ideological neutrality, yet this may introduce automation bias by suppressing cognitive engagement in human decision-making. We conducted randomized trials with 2,500 participants to test whether culturally biased AI enhances human decision-making. Participants interacted with politically diverse GPT-4o variants on information evaluation tasks. Partisan AI assistants enhanced human performance, increased engagement, and reduced evaluative bias compared to non-biased counterparts, with amplified benefits when participants encountered opposing views. These gains carried a trust penalty: participants underappreciated biased AI and overcredited neutral systems. Exposing participants to two AIs whose biases flanked human perspectives closed the perception-performance gap. These findings complicate conventional wisdom about AI neutrality, suggesting that strategic integration of diverse cultural biases may foster improved and resilient human decision-making.
Cite
@article{arxiv.2508.09297,
title = {Biased AI improves human decision-making but reduces trust},
author = {Shiyang Lai and Junsol Kim and Nadav Kunievsky and Yujin Potter and James Evans},
journal= {arXiv preprint arXiv:2508.09297},
year = {2025}
}