研究信息不对称如何影响用户对AI产品的信任与采用
When Life Gives You AI, Will You Turn It Into A Market for Lemons? Understanding How Information Asymmetries About AI System Capabilities Affect Market Outcomes and Adoption
- 通过模拟市场实验，测试不同披露程度下用户对AI质量的判断
- 发现信息不透明会严重抑制AI采纳，部分披露可显著提升决策效率
- 为政策制定者提供实证依据，适合关注AI治理与用户信任的研究者
AI消费者市场存在严重的买卖双方信息不对称。复杂的AI系统可能看似高度准确，却存在高昂错误或隐藏缺陷。尽管已有监管努力推动信息披露，但巨大信息鸿沟依然存在。本文首次通过实验揭示信息不对称与披露设计在塑造用户采纳AI系统中的关键作用。我们在模拟的AI产品市场中系统性地改变低质量AI系统的密度和披露要求深度，考察人们在误用低质量AI系统风险下的反应。随后将参与者的选择与理性贝叶斯模型对比，分析部分信息披露如何改善AI采纳。结果表明，信息不对称对AI采纳具有显著负面影响，但适度披露设计能有效提升人类决策的整体效率。
原文摘要 · Abstract (English)
AI consumer markets are characterized by severe buyer-supplier market asymmetries. Complex AI systems can appear highly accurate while making costly errors or embedding hidden defects. While there have been regulatory efforts surrounding different forms of disclosure, large information gaps remain. This paper provides the first experimental evidence on the important role of information asymmetries and disclosure designs in shaping user adoption of AI systems. We systematically vary the density of low-quality AI systems and the depth of disclosure requirements in a simulated AI product market to gauge how people react to the risk of accidentally relying on a low-quality AI system. Then, we compare participants' choices to a rational Bayesian model, analyzing the degree to which partial information disclosure can improve AI adoption. Our results underscore the deleterious effects of information asymmetries on AI adoption, but also highlight the potential of partial disclosure designs to improve the overall efficiency of human decision-making.
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