agentic AI让医生更信任临床决策，透明推理过程提升信赖度。
Agentic AI Enhances Physician Trust in Clinical Decision Making
- 医生可看到AI如何调用工具、逐步推理，过程透明增强信任。
- 90%以上治疗方案选择中，医生更倾向使用具透明推理的AI。
- 虽透明性提升信任，但错误输出仍导致过度依赖，需人工监督。
医学AI已从传统推理模式转向代理型AI（agentic AI），该模式在推理过程中自主调用外部工具，并使中间推理步骤与工具输出对用户透明。尽管实证表明其性能优于以往模型，但医生对代理型AI的信任程度尚未充分研究。为此，三位医生评估了315个多模态临床案例，量化了过程导向的认知信任与结果导向的行为依赖。对比非代理型基线，医生对代理型AI表现出显著更高的认知信任和行为依赖（P < 0.001）。尤其在治疗规划任务中，医生最信任代理型推理，在89.57%的案例中优先选择。此外，过程导向的认知信任与结果导向的行为依赖显著相关（P < 0.001）。然而，仍存在对错误代理输出的可测量过度依赖，凸显仅靠决策逻辑透明不足以完全保障安全，强调持续需要严格的临床人员监督。
原文摘要 · Abstract (English)
Medical AI has shifted from reasoning to agentic AI, a new paradigm that autonomously invokes external tools during reasoning, rendering intermediate reasoning steps and tool outputs transparent to users. Although proven to outperform previous models, physician trust in agentic AI remains largely unexplored. To address this, three physicians evaluated 315 multimodal clinical cases quantifying both process-oriented cognitive trust and outcome-oriented behavioral reliance. Comparing agentic AI against non-agentic baselines, physicians exhibited significantly higher cognitive and behavioral trust for the agentic model (P < 0.001). Specifically, on treatment planning tasks, physicians trusted the agentic reasoning most, preferring it in 89.57% of cases. Furthermore, process-oriented cognitive trust is significantly associated with outcome-oriented behavioral reliance (P < 0.001). However, measurable over-reliance on incorrect agentic outputs still exists, highlighting the inherent limitations of decision-logic transparency alone and underscoring the continuous need for rigorous clinician oversight.
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