Artificial intelligence in medicine: An ethical and legal review.
TL;DR
This review addresses the primary ethical principles relevant to AI in medicine - including respect for patient autonomy, beneficence, non-maleficence, and justice - alongside key legal frameworks with respect to liability, data protection, regulatory compliance, and algorithmic transparency.
Abstract
The integration of artificial intelligence (AI) and machine learning (ML) into medical practice marks a transformative shift within healthcare delivery, diagnostics, and treatment paradigms. Although AI systems exhibit sophisticated capabilities in image recognition, predictive analytics, and clinical decision support, their implementation introduces fundamental ethical and legal questions requiring thorough examination. This review addresses the primary ethical principles relevant to AI in medicine - including respect for patient autonomy, beneficence, non-maleficence, and justice - alongside key legal frameworks with respect to liability, data protection, regulatory compliance, and algorithmic transparency. It analyzes challenges such as algorithmic bias, patient privacy, informed consent in automated decision-making, and the evolving responsibilities of healthcare professionals in AI-based clinical environments. Additionally, the review investigates emerging regulatory approaches across jurisdictions, considering how existing medical device regulations, data protection laws, and professional liability frameworks are adapting to AI technologies. The paper concludes with recommendations for clinicians, policymakers, and developers to promote ethical AI deployment that strengthens the physician-patient relationship and advances healthcare equity.