人机协作研究：不同任务需要不同的信任校准 Supporting Calibrated Reliance in Human-AI Collaboration: Different Strategies for Different Tasks

精读摘要

AI 越来越多地辅助人类决策，核心难题是：什么样的信息能帮人知道何时该信赖 AI 预测、何时该质疑或推翻它。研究团队做了三项受控人类实验，覆盖 RAVEN 矩阵的抽象视觉推理与 LSAT 逻辑推理，考察不同形式的 AI 支持如何影响人机团队表现。一项多阶段揭示研究表明，AI 预测与解释会同时影响客观准确度与主观信任，而最优支持策略因任务类型而异。 As AI supports human decision making, a central challenge is what information helps people know when to rely on AI and when to override it. Across three controlled human-subject studies spanning RAVEN matrices and LSAT problems, the authors examine how different forms of AI support affect human-AI team performance. A multi-stage reveal study shows AI predictions and explanations affect both objective accuracy and subjective trust, and optimal support strategies differ by task.