Artificial Intelligence and the Future of Public Health: A Qualitative Inquiry into Ethical, Social, and Policy Scenarios

Abstract

This study explores the ethical, social, and policy implications of artificial intelligence (AI) in public health. This qualitative study employed semi-structured interviews with 32 experts in AI research, public health policy, bioethics, and healthcare administration. Participants were recruited through online announcements and professional platforms, ensuring a diverse representation of viewpoints. Data collection continued until theoretical saturation was achieved. Interviews were transcribed verbatim and analyzed using NVivo software through thematic analysis, following an inductive coding approach to identify key ethical, social, and policy concerns. The analysis revealed three main themes: ethical scenarios, social scenarios, and policy scenarios. Ethical concerns included bias in AI models, privacy and data security risks, and trust in AI-driven healthcare, with participants emphasizing the need for bias mitigation strategies and transparent AI governance. Socially, the findings highlighted AI’s impact on the healthcare workforce, disparities in AI accessibility, and the evolving patient-doctor relationship, raising concerns about public trust and the digital divide. Policy challenges centered on the lack of standardized AI regulations, unclear accountability mechanisms, and the need for global collaboration in AI governance, with participants advocating for clearer compliance frameworks and cross-border AI policy alignment. While AI holds transformative potential in public health, its successful integration requires ethical safeguards, inclusive social adaptation, and comprehensive policy frameworks. Addressing algorithmic bias, strengthening data security, fostering public trust, and establishing robust governance structures are essential for ensuring that AI-driven public health interventions align with ethical principles, social equity, and regulatory standards.