Ethics of AI in healthcare: a scoping review demonstrating applicability of a foundational framework
Aaron J. Gorelik, Mengyuan Li, Jessica Hahne, Junyi Wang, Yongqi Ren, Lei Yang, Xin Zhang, Xing Liu, Xiaomin Wang, Ryan Bogdan, Brian Carpenter
Abstract
Artificial Intelligence (AI) is increasingly being adopted across many industries including healthcare. This has brought forth the development of many new independent ethical frameworks for responsible use of AI within institutions and companies. Risks associated with the application of AI in healthcare have high stakes for patients. Further, the existence of multiple frameworks may exacerbate these risks due to potential differences in interpretation and prioritization in said frameworks. Resolving these risks requires an ethical framework that is both broadly adopted in healthcare settings and applicable to AI. Here, we examined whether a framework consisting of the 4 well-established principles of biomedical ethics (i.e., Beneficence, Non-Maleficence, Respect for Autonomy, and Justice) can serve as a foundation for an ethical framework for AI in healthcare. To this end, we conducted a scoping review of 227 peer-reviewed papers using semi-inductive thematic analyses to categorize patient-related ethical issues in healthcare AI under these 4 principles of biomedical ethics. We found that these principles, which are already widely adopted in healthcare settings, were comprehensively and internationally applicable to ethical considerations concerning use of AI in healthcare. The existing four principles of biomedical ethics can provide a foundational ethical framework for applying AI in healthcare, grounding other Responsible AI frameworks, and can act as a basis for AI governance and policy in healthcare.