Ethical Use of Artificial Intelligence in Public Health: Mitigating Risks and Advancing Health Equity

Artificial intelligence (AI) is increasingly integrated into public health practice, offering new tools for surveillance, behavioral interventions, disease prevention, risk communication, and population health management. Although AI demonstrates promise for earlier disease detection, improved intervention targeting, and cost-effective augmentation of limited public health capacity, many tools are being deployed amid fragmented regulatory frameworks, validation standards, and equity safeguards that govern other health interventions. Consequently, AI can introduce significant ethical, operational, and equity-related risks. Current industry-driven AI development lacks sufficient guardrails for the ethical and responsible use of AI across public health systems, creating risks that disproportionately affect underserved populations. We examine current AI applications in public health through the lens of established ethical principles, with particular attention to historically marginalized communities. In our analyses, we identify critical infrastructure and governance gaps across federal, state, local, and Tribal settings, and propose concrete strategies, including mandatory equity impact assessments, validation in the communities of intended use, alignment with data sovereignty principles, transparency with communities about when and how AI is used, and sustained investment in public health workforce capacity to evaluate AI tools. (Am J Public Health. 2026;116(10):1520-1528. https://doi.org/10.2105/AJPH.2026.308638).