Artificial Intelligence in Public Health Education: A Scoping Review of Workforce Competency Development

Area of Science:

• Public Health Education
• Artificial Intelligence
• Workforce Development

Background:

• Artificial intelligence (AI) is revolutionizing public health education, necessitating new strategies for a digitally competent workforce.
• AI offers adaptive, personalized, and scalable learning but raises underexplored long-term implications and equity concerns.

Purpose of the Study:

• To conduct a scoping review mapping the literature on AI's role in public health education.
• To analyze AI's impact on workforce competency development and identify associated challenges.

Main Methods:

• Utilized Arksey and O'Malley's framework with Levac et al. enhancements.
• Conducted a comprehensive literature search across PubMed, Scopus, and IEEE Xplore (Jan 2015 - May 2025).
• Applied PRISMA-ScR guidelines for study screening and thematic analysis of 26 included studies.

Main Results:

• AI transforms pedagogy via simulations and adaptive platforms, driving AI-specific and digital literacy training.
• Identified institutional disparities in AI readiness and significant ethical concerns regarding algorithmic bias and equitable access.
• Highlighted the importance of interdisciplinary collaboration and curriculum reform for sustained AI integration.

Conclusions:

• AI presents significant opportunities for public health education enhancement.
• Integration requires careful attention to equity, institutional capacity, and ethical responsibility.
• Strategic policy, curriculum reform, and continued research are vital for preparing the future public health workforce.