Ethical Challenges to the Adoption of AI in Healthcare: A Review

There are few comprehensive summaries of the ethical challenges associated with the adoption of artificial intelligence in healthcare. This review utilizes a systematic search focused on identifying the barriers and facilitators to the implementation of artificial intelligence in healthcare, highlighting the diversity of ethical challenges and the complex interactions between practical challenges and ethics issues. For example, the quality of the data upon which artificial intelligence models are developed relates to several ethics principles, as does the issue of gaining user trust. Importantly, there is also the difficulty of achieving the right balance between the discussed principles, since one might not be able to maximize one principle without having to sacrifice another. For example, maximizing privacy might require minimizing data collection from patients, which might negatively affect beneficence. As such, this review highlights the variety and complexity of ethical issues associated with artificial intelligence implementation in healthcare.

目前针对医疗领域人工智能（Artificial Intelligence）落地应用所涉及的伦理挑战，尚未有全面系统的总结。本综述采用系统性检索策略，旨在识别医疗领域人工智能部署应用的阻碍因素与促进条件，并着重阐明伦理挑战的多样性，以及实践挑战与伦理议题间的复杂互作关系。例如，人工智能模型训练所依赖的数据质量，关乎多项伦理原则；获取用户信任的相关议题亦是如此。尤为关键的是，在上述伦理原则间达成恰当平衡亦存在难度——因为若不牺牲某一项原则，便无法最大化另一项原则的落实效果。例如，若要最大化保护患者隐私，可能需要尽可能减少患者数据的采集量，这会对行善原则（beneficence）的落实产生负面影响。综上，本综述阐明了医疗领域人工智能部署应用所涉及的各类伦理议题的多样性与复杂性。