Artificial intelligence is already ubiquitous, and is increasingly being used to autonomously make ever more consequential decisions. However, there has been relatively little research into the consequences for equity of the use of narrow AI and automated decision systems in medicine and public health. A narrative review using a hermeneutic approach was undertaken to explore current and future uses of AI in medicine and public health, issues that have emerged, and longer-term implications for population health. Accounts in the literature reveal a tremendous expectation on AI to transform medical and public health practices, especially regarding precision medicine and precision public health. Automated decisions being made about disease detection, diagnosis, treatment, and health funding allocation have significant consequences for individual and population health and wellbeing. Meanwhile, it is evident that issues of bias, incontestability, and erosion of privacy have emerged in sensitive domains where narrow AI and automated decision systems are in common use. As the use of automated decision systems expands, it is probable that these same issues will manifest widely in medicine and public health applications. Bias, incontestability, and erosion of privacy are mechanisms by which existing social, economic and health disparities are perpetuated and amplified. The implication is that there is a significant risk that use of automated decision systems in health will exacerbate existing population health inequities. The industrial scale and rapidity with which automated decision systems can be applied to whole populations heightens the risk to population health equity. There is a need therefore to design and implement automated decision systems with care, monitor their impact over time, and develop capacities to respond to issues as they emerge.

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自动化决策系统对人口健康公平带来的风险：叙事评论

人工智能已经无处不在，并且越来越多地用于自主做出更重要的决策。然而，关于在医学和公共卫生领域使用狭义人工智能和自动化决策系统对公平的影响的研究相对较少。使用解释学方法进行了叙述性审查，以探索人工智能在医学和公共卫生中的当前和未来用途、出现的问题以及对人口健康的长期影响。文献中的描述揭示了人们对人工智能改变医疗和公共卫生实践的巨大期望，尤其是在精准医疗和精准公共卫生方面。关于疾病检测、诊断、治疗的自动化决策，卫生资金分配对个人和人口的健康和福祉产生重大影响。同时，很明显，在普遍使用狭义人工智能和自动决策系统的敏感领域中，偏见、不可争辩和隐私侵蚀问题已经出现。随着自动决策系统的使用扩大，这些相同的问题很可能会在医学和公共卫生应用中广泛出现。偏见、无可争辩和隐私侵蚀是现有的社会、经济和健康差异得以延续和放大的机制。这意味着在健康领域使用自动化决策系统存在着加剧现有人口健康不平等的重大风险。自动化决策系统可以应用于整个人群的工业规模和速度增加了人口健康公平的风险。因此，需要谨慎地设计和实施自动化决策系统，监测其影响随着时间的推移，并发展应对出现问题的能力。