Artificial intelligence (AI) could revolutionise health care, potentially improving clinician decision making and patient safety, and reducing the impact of workforce shortages. However, policymakers and regulators have concerns over whether AI and clinical decision support systems (CDSSs) are trusted by stakeholders, and indeed whether they are worthy of trust. Yet, what is meant by trust and trustworthiness is often implicit, and it may not be clear who or what is being trusted. We address these lacunae, focusing largely on the perspective(s) of clinicians on trust and trustworthiness in AI and CDSSs. Empirical studies suggest that clinicians’ concerns about their use include the accuracy of advice given and potential legal liability if harm to a patient occurs. Onora O’Neill’s conceptualisation of trust and trustworthiness provides the framework for our analysis, generating a productive understanding of clinicians’ reported trust issues. Through unpacking these concepts, we gain greater clarity over the meaning ascribed to them by stakeholders; delimit the extent to which stakeholders are talking at cross purposes; and promote the continued utility of trust and trustworthiness as useful concepts in current debates around the use of AI and CDSSs.

中文翻译：

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人工智能和临床决策支持：临床医生对信任、可信度和责任的看法

人工智能 (AI) 可以彻底改变医疗保健，有可能改善临床医生的决策和患者安全，并减少劳动力短缺的影响。然而，政策制定者和监管机构对人工智能和临床决策支持系统（CDSS）是否受到利益相关者的信任以及它们是否值得信任表示担忧。然而，信任和值得信赖的含义通常是隐含的，并且可能不清楚谁或什么值得信任。我们解决了这些缺陷，主要关注临床医生对人工智能和 CDSS 的信任和可信度的看法。实证研究表明，临床医生对其使用的担忧包括所提供建议的准确性以及对患者造成伤害时可能承担的法律责任。奥诺拉·奥尼尔对信任和可信度的概念化为我们的分析提供了框架，从而对临床医生报告的信任问题产生了富有成效的理解。通过解析这些概念，我们可以更清楚地了解利益相关者赋予它们的含义；限制利益相关者相互矛盾的谈话程度；并促进信任和可信度作为当前围绕人工智能和 CDSS 使用的辩论中的有用概念的持续利用。