临床医生与AI判断分歧事件的价值如何被记录和利用
Realizing the value of the divergence event in clinical human-AI interaction
医生和AI意见不合时，现在的系统只存结果不存过程。这篇 npj Digital Medicine 的文章提出把分歧记录下来，对做医疗AI的人来说思路很新鲜。
发表在 npj Digital Medicine 的文章指出，当临床医生判断与 AI 输出出现分歧时，现有界面只记录最终决策，双方各自的贡献信息随决策消失。作者提出应为 clinician-AI 交互建立独立的记录，将分歧事件本身可视化。文中论证分歧可视化可以支持透明的患者沟通、为道德责任提供依据、可能减轻法律责任，并将分歧视为临床 AI 中信号量最高的时刻。
Realizing the value of the divergence event in clinical human-AI interaction
npj Digital Medicine, Published online: 13 October 2026; doi:10.1038/s41746-026-03394-8 When a clinician’s judgment and AI output diverge, what each side contributed disappears with the decision, because current interfaces capture the outcome and not the interaction. We propose that the clinician-AI interaction requires its own account and describe how divergence can be made visible. Making the divergence event visible supports transparent patient communication, better grounds moral responsibility, may mitigate liability, and reframes divergence as clinical AI’s highest-signal moment.
