有偏AI能提升人类决策质量，但降低信任度。
Biased AI improves human decision-making but reduces trust
- 用政治倾向性GPT-4o测试人类判断力，激发更主动参与。
- 面对对立观点时，偏见型AI使人类表现更好，偏差更小。
- 偏见模型被低估，中立模型被高估，暴露双面偏见可弥合差距。
当前AI系统为降低风险而追求意识形态中立，但这可能引发自动化偏见，抑制人类认知参与。我们对2500名参与者进行随机实验，测试文化偏见型AI是否能提升人类决策。参与者与政治多元的GPT-4o变体交互于信息评估任务中。具有立场的AI助手提升了人类表现，增强参与度，并减少评估偏差，尤其在接触对立观点时效果更显著。然而，这些优势伴随信任代价：参与者低估了偏见型AI，高估了中立系统。当参与者同时接触两种偏见方向覆盖其自身立场的AI时，感知与实际表现之间的差距得以缩小。研究挑战了传统对AI中立性的认知，表明有策略地融入多元文化偏见，或可促进更优且更具韧性的决策能力。
原文摘要 · Abstract (English)
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.
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