Couture Vincent, Roy Marie-Christine, Dez Emma, Tremblay Fannie, Bélisle-Pipon Jean-Christophe
Faculty of Nursing, Université Laval, Québec, QC, Canada.
Faculty of Arts and Sciences, Université de Montréal, Montreal, QC, Canada.
Front Sociol. 2025 Sep 9;10:1536389. doi: 10.3389/fsoc.2025.1536389. eCollection 2025.
Artificial intelligence systems (AIS) powered by big data (BD) are more and more common in the healthcare sector and many anticipate that they will have a substantial effect on population health. Facing the disruptive potential of these transformations, there is a need to keep the pace with the ethical reflection accompanying the uses of AIS and the BD systems enabling such innovations.
To carry out this task, we conducted a scoping review of the ethical issues of AIS and BD, in population health, based on 243 scholarly articles.
Our results show the explosion of publications on the subject in recent years. Our qualitative analysis of this literature highlights the potential issues of AIS and BD on the three components of population health: (1) the health outcomes and their distribution in the population and between populations; (2) the patterns of health determinants; (3) the policies and interventions developed to connect the previous components.
Our conclusions show the uncertainty of the positive outcomes of these technologies and their potential for unequal distribution. Authors consider that AIS and BD will affect determinants of health either in their understanding and by transforming the structure of these determinants. At last, this review points that the policies and interventions developed to attain population health goals will have to answer to numerous ethical expectations. This review offers a comprehensive mapping of ethical issues raised by the uses of AIS in the global field of population health.
由大数据驱动的人工智能系统在医疗保健领域越来越普遍，许多人预计它们将对人群健康产生重大影响。面对这些变革的潜在颠覆性，有必要跟上伴随人工智能系统及促成此类创新的大数据系统使用的伦理思考步伐。
为完成这项任务，我们基于243篇学术文章，对人群健康领域中人工智能系统和大数据的伦理问题进行了范围综述。
我们的结果显示近年来关于该主题的出版物激增。我们对这些文献的定性分析突出了人工智能系统和大数据在人群健康的三个组成部分上的潜在问题：（1）健康结果及其在人群内部和人群之间的分布；（2）健康决定因素模式；（3）为连接前两个组成部分而制定的政策和干预措施。
我们的结论表明这些技术积极成果的不确定性及其不平等分配的可能性。作者认为人工智能系统和大数据将在理解健康决定因素以及改变这些决定因素的结构方面影响健康决定因素。最后，本综述指出为实现人群健康目标而制定的政策和干预措施将必须回应众多伦理期望。本综述全面梳理了全球人群健康领域中使用人工智能系统引发的伦理问题。
