Liability Framework to Regulate Artificial Intelligence in Healthcare
TL;DR
Analysis of six areas of artificial intelligence in healthcare concludes that a workable framework must combine the principles of medical negligence law with data protection, consumer protection and sectoral safety requirements, together with governance mechanisms for artificial intelligence such as human oversight, audit logs, explainability and grievance redressal.
Abstract
Artificial intelligence is beginning to play an important role in contemporary healthcare, where it is applied to diagnosis, clinical support, triage, imaging, remote monitoring, drug development and hospital management. A problem of liability arises because artificial intelligence produces outputs that can contribute to patient risk, yet the system itself cannot bear liability in the way a medical professional, a hospital or a manufacturer does. A review of the literature shows that no dedicated regime governs artificial intelligence liability in healthcare, and it brings out the associated questions of justice, bias, accountability, transparency and information security. This article analyses six areas: patient data confidentiality, patient consent, algorithmic bias and discrimination, misdiagnosis, accountability, and the reuse of previous patient records. It concludes that a workable framework must combine the principles of medical negligence law with data protection, consumer protection and sectoral safety requirements, together with governance mechanisms for artificial intelligence such as human oversight, audit logs, explainability and grievance redressal. The approach is qualitative and comparative, resting on a study of the literature and a content analysis of existing legal instruments, including the Digital Personal Data Protection Act, 2023, the Ayushman Bharat Digital Mission privacy framework, and the guidance of the World Health Organization on artificial intelligence in health. The findings indicate that the existing legal framework offers a partial answer to these questions but not an integrated one. Healthcare artificial intelligence should be treated as a high-risk setting governed by layered liability: the developer answers for design defects and bias, the deploying entity, ordinarily the hospital, answers for implementation and monitoring, and the medical professional answers for negligence where the use of artificial intelligence still involves human judgment.