标题： 智能推理提示：人工智能信息在复杂决策中的作用框架与案例研究 显示英文标题

标题： Intelligent Reasoning Cues: A Framework and Case Study of the Roles of AI Information in Complex Decisions

摘要： 基于人工智能（AI）的决策支持系统可能高度准确，但仍无法有效支持用户或改善决策。 现有的AI辅助决策理论侧重于校准对AI建议的依赖，这使得不同系统设计如何影响背后的推理过程尚不明确。 我们通过重新考虑AI界面作为智能推理提示的集合来解决这一差距：单独的AI信息片段，可以分别影响决策。 然后，我们在高风险的临床决策（在重症监护中治疗败血症患者）中探讨了八种推理提示的作用。 通过与六支团队的上下文访谈和25名医生的自言自语研究，我们发现推理提示具有不同的影响模式，可以直接指导设计。 我们的结果还表明，推理提示应优先处理高变异性及需要判断的任务，适应以确保与不断变化的决策需求相兼容，并为复杂病例提供互补且严谨的见解。 显示英文摘要

摘要： Artificial intelligence (AI)-based decision support systems can be highly accurate yet still fail to support users or improve decisions. Existing theories of AI-assisted decision-making focus on calibrating reliance on AI advice, leaving it unclear how different system designs might influence the reasoning processes underneath. We address this gap by reconsidering AI interfaces as collections of intelligent reasoning cues: discrete pieces of AI information that can individually influence decision-making. We then explore the roles of eight types of reasoning cues in a high-stakes clinical decision (treating patients with sepsis in intensive care). Through contextual inquiries with six teams and a think-aloud study with 25 physicians, we find that reasoning cues have distinct patterns of influence that can directly inform design. Our results also suggest that reasoning cues should prioritize tasks with high variability and discretion, adapt to ensure compatibility with evolving decision needs, and provide complementary, rigorous insights on complex cases.