Medical AI, standard of care in negligence and tort law

• Main Author: CHAN, Gary Kok Yew
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Tort Law; Standard of Care; Medical Negligence; Artificial Intelligence; Vicarious Liability; Non-delegable duties; Artificial Intelligence and Robotics; Medical Jurisprudence; Torts
• Online Access: https://ink.library.smu.edu.sg/sol_research/3457; https://search.library.smu.edu.sg/discovery/fulldisplay?docid=alma99481301102601&context=L&vid=65SMU_INST:SMU_NUI&lang=en&search_scope=Everything&adaptor=Local%20Search%20Engine&tab=Everything&query=any,contains,AI,%20Data%20and%20Private%20Law:%20Translating%20Theory%20into%20Practice&offset=0
• Institution: Singapore Management University

AI is increasingly utilised in the provision of medical services to diagnose diseases, treat illnesses and perform surgery. There is growing evidence that AI can outperform human doctors in diagnoses. Nonetheless, AI is not immune from errors. This paper discusses the potential tort liabilities of doctors and hospitals arising from the use of AI in medical services provision, in particular, the standard of care expected of them under the tort of negligence applicable to Singapore and Malaysia. This issue is examined by reference to competing considerations such as efficiency, the promotion of medical innovations, the relevance of ethical guidelines applicable to the medical profession and patient welfare. It is proposed that the standard of care principles in the common law tort of negligence provide a fault-based framework that is sufficiently flexible to accommodate the use of AI innovations in healthcare. The criteria for determining the appropriate standard of care allow for a judicious balance amongst the competing considerations. On the other hand, the doctrines of vicarious liability and non-delegable duties do not in themselves support making the hospitals and doctors strictly liable in tort for injuries suffered by patients arising from the use of medical AI.