Scoping Review: Legal and Ethical Principles of Artificial Intelligence in Public Health

Abstract

The growing accessibility of large health datasets and AI's ability to analyze them offers significant potential to transform public health and epidemiology. AI-driven interventions in preventive, diagnostic, and therapeutic healthcare are becoming more prevalent, but they raise ethical concerns, particularly regarding patient safety and privacy. This study presents a thorough analysis of ethical and legal principles found in the literature on AI applications in public health. A comprehensive search yielded 22 publications for review, revealing ethical principles such as equity, bias, privacy, security, safety, transparency, confidentiality, accountability, social justice, and autonomy. Additionally, five key ethical challenges were identified. The study emphasizes the importance of addressing these ethical and legal concerns and encourages further research to establish comprehensive guidelines for responsible AI implementation in public health.