研究心理特质如何影响人对AI决策的自信程度与判断准确性
Beyond Awareness: Investigating How AI and Psychological Factors Shape Human Self-Confidence Calibration
- 通过两组实验考察认知风格与自我信心校准的关系
- 高自我信心校准者决策准确率提升，且情绪感知更合理
- 适合设计个性化AI系统时参考个体心理特征
人类与AI协作的效果高度依赖于人在决策前的自我信心校准情况，这决定了其对AI建议的信任或抗拒。本研究开展两项实验，探究决策前自我信心校准水平、需要认知程度（Need for Cognition, NFC）和开放性思维（Actively Open-Minded Thinking, AOT）是否影响决策准确性、自我信心恰当性以及元认知感知（全局与情感层面）。第一项研究提出识别校准良好用户的策略，并比较不同NFC与AOT水平下的决策表现。第二项研究在无AI、两阶段AI和个性化AI三种情境下，分析自我信心校准的影响，并考虑NFC与AOT的调节作用。结果表明，在设计AI辅助决策系统时，人的自我信心校准状态及心理特质具有关键意义。研究进一步提出设计建议，以应对自我信心校准挑战，支持面向个体差异的用户中心型AI。
原文摘要 · Abstract (English)
Human-AI collaboration outcomes depend strongly on human self-confidence calibration, which drives reliance or resistance toward AI's suggestions. This work presents two studies examining whether calibration of self-confidence before decision tasks, low versus high levels of Need for Cognition (NFC), and Actively Open-Minded Thinking (AOT), leads to differences in decision accuracy, self-confidence appropriateness during the tasks, and metacognitive perceptions (global and affective). The first study presents strategies to identify well-calibrated users, also comparing decision accuracy and the appropriateness of self-confidence across NFC and AOT levels. The second study investigates the effects of calibrated self-confidence in AI-assisted decision-making (no AI, two-stage AI, and personalized AI), also considering different NFC and AOT levels. Our results show the importance of human self-confidence calibration and psychological traits when designing AI-assisted decision systems. We further propose design recommendations to address the challenge of calibrating self-confidence and supporting tailored, user-centric AI that accounts for individual traits.
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