医疗AI需靠设计与责任赢得信任，而非模仿人类情感。
Not someone, but something: Rethinking trust in the age of medical AI
- 提出信任是动态构建的，非简单转移
- 强调透明、问责与医疗价值观对齐
- 适合关注医工交叉伦理的研究者
随着人工智能在医疗中的深入应用，医学决策中的信任关系正迅速演变。这一变化在放射学领域尤为显著，AI工具已嵌入影像工作流的各个环节——从预约、采集、解读、报告到与转诊医生及患者的沟通。本文认为，对AI的信任并非从人到机器的简单转移，而是一种需要持续建立和维护的动态关系。与其争论AI是否应进入医学，不如探讨：AI必须赢得何种信任？如何赢得？基于哲学、生物伦理与系统设计的视角，文章分析了人类信任与机器可靠性之间的关键差异，强调透明度、问责机制以及与优质医疗价值的一致性。文章主张，对AI的信任不应依赖于模仿共情或直觉，而应建立在审慎设计、负责任部署和明确道德责任之上。目标是实现平衡视角，既避免盲目乐观，也拒绝无端恐惧。对AI的信任应被视为一种需经时间积累的成果，而非理所当然的前提。
原文摘要 · Abstract (English)
As artificial intelligence (AI) becomes embedded in healthcare, trust in medical decision-making is changing fast. Nowhere is this shift more visible than in radiology, where AI tools are increasingly embedded across the imaging workflow - from scheduling and acquisition to interpretation, reporting, and communication with referrers and patients. This opinion paper argues that trust in AI isn't a simple transfer from humans to machines - it is a dynamic, evolving relationship that must be built and maintained. Rather than debating whether AI belongs in medicine, it asks: what kind of trust must AI earn, and how? Drawing from philosophy, bioethics, and system design, it explores the key differences between human trust and machine reliability - emphasizing transparency, accountability, and alignment with the values of good care. It argues that trust in AI should not be built on mimicking empathy or intuition, but on thoughtful design, responsible deployment, and clear moral responsibility. The goal is a balanced view - one that avoids blind optimism and reflexive fear. Trust in AI must be treated not as a given, but as something to be earned over time.
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