The ethical challenge of AI in medicine: Who owns the mistakes?

To the Editor, Artificial intelligence encompasses machine learning and natural language processing to simulate human cognition. It is revolutionizing medicine by supporting diagnosis and data management in healthcare. Its advantages include shorter hospital stays and reduced use of invasive procedures, which ultimately lower treatment costs, increase efficiency, and improve patient outcomes and quality of life. Despite these benefits, AI may produce errors with serious consequences, highlighting challenges regarding accountability when issues such as responsibility and liability arise in clinical practice. The application of artificial intelligence in medical fields creates serious ethical, social, and legal challenges, which include concerns regarding patient privacy and data security, algorithmic bias, and fair access to AI-powered medical treatment. The existing problems demonstrate the requirement for strong regulatory systems and explicit responsibility guidelines, which will guarantee that medical institutions use artificial intelligence technologies in a responsible manner. 1 Currently, AI applications are being utilized clinically for disease screening and triage, diagnosis, risk assessment, and treatment planning. Notable examples include the IDx-DR diagnostic system for diabetic retinopathy screening, the CC-Cruiser for childhood cataract detection, and MySurgeryRisk for preoperative risk evaluation. Literature also highlights AI applications in cancer, neurological disorders, eye diseases, infections, and musculoskeletal conditions. These tools support clinical decision-making, enhance diagnostic efficiency and accuracy, and are reshaping modern healthcare delivery. 2 Despite these benefits, there is a pressing need to improve these systems due to various legal and ethical concerns, such as built-in biases, a lack of privacy and transparency, data leaks, and uncertain accuracy, all of which should be thoroughly validated and continuously evaluated. Legal and ethical frameworks for artificial intelligence in healthcare currently face development challenges, which lead to multiple uncertainties regarding liability requirements. Naik et al. demonstrate that AI system errors create complicated problems because they require determination of which party should take responsibility; a determination that involves deciding whether liability falls on the healthcare provider using the tool,