Investigating the use of generative AI policies among ASPPH member schools and programs of public health

Authors

• Ashish Joshi, School of Public Health, University of Memphis, Memphis, TN, United States.
• Brian McGoldrick, School of Public Health, University of Memphis, Memphis, TN, United States.
• Nidhi Mittal, School of Public Health, University of Memphis, Memphis, TN, United States.
• Shongkour Roy, School of Public Health, University of Memphis, Memphis, TN, United States.
• Zebunnesa Zeba, School of Public Health, University of Memphis, Memphis, TN, United States.
• Michael Arthur Ofori, School of Public Health, University of Memphis, Memphis, TN, United States.
• Stella Dockery, School of Public Health, University of Memphis, Memphis, TN, United States.
• Niharika Jha, School of Public Health, University of Memphis, Memphis, TN, United States.
• John Auerbach, ICF, Fairfax, VA, United States.
• Jean Cadet, School of Population Health, Andrews University, Berrien Springs, MI, United States.
• Jessica Kruger, Teaching Innovation and Excellence, School of Public Health and Health Professions, University at Buffalo, New York, NY, United States.
• Robert Leeman, Public Health and Health Sciences, Bouvé College of Health Sciences, Northeastern University, Boston, MA, United States.
• Kerry Mitchell, Department of Public Health and Preventive Medicine, St. George's University, St. George's, Grenada.
• Guillaume Molter, Administrative and Web Services, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
• Andrew Naidech, Program in Public Health, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
• Elahe Nezami, Department of Health Sciences, University of Miami, Miami, FL, United States.
• Sylvester Orimaye, College of Global Population Health at UHSP in St. Louis, St. Louis, MO, United States.
• Courtney Queen, Julia Jones Matthews School of Population and Public Health, Texas Tech University Health Sciences Center, Lubbock, TX, United States.
• Umair Shah, Phamily, Cincinnati, OH, United States.
• Abdul Shaikh, Global Leader for Population Health, Amazon Web Services (AWS), Seattle, WA, United States.
• Daniel Smith, College of Graduate Health Studies, A.T. Still University, Mesa, AZ, United States.
• Melissa Tracy, Department of Epidemiology and Biostatistics, University at Albany College of Integrated Health Sciences, Albany, NY, United States.
• Edward Trapido, Louisiana State University Health Sciences Center School of Public Health, New Orleans, LA, United States.
• Jorg Westermann, School of Health Sciences, Walden University College of Health Sciences and Public Policy, Minneapolis, MN, United States.
• Andrew Wiss, Milken Institute School of Public Health, George Washington University, Washington, DC, United States.
• Jonathan Zaccarini, School of Public Health, Columbia University Mailman, New York, NY, United States.
• Tim E. Leshan, Association of Schools and Programs of Public Health, Washington, DC, United States.
• Linda A. Alexander, Association of Schools and Programs of Public Health, Washington, DC, United States.
• Jamie M. Atchison, Association of Schools and Programs of Public Health, Washington, DC, United States.
• Eduardo Ruiz, Association of Schools and Programs of Public Health, Washington, DC, United States.
• Laura Magana, Association of Schools and Programs of Public Health, Washington, DC, United States.

Document Type

Journal Article

Publication Date

1-1-2026

Journal

Frontiers in public health

Volume

14

DOI

10.3389/fpubh.2026.1796810

Keywords

AI; AI use; ASPPH; generative AI; policy; public health

Abstract

BACKGROUND: The integration of generative artificial intelligence (AI) into the operational and curricular foundations of higher education is a dynamically evolving issue, particularly in public health programs looking to ethically embrace the ever-growing potential of AI in health research and education. Despite a collective priority across the United States to effectively adopt generative AI, few works have characterized the scope and rigor of existing guidance. METHODS: This study employs a mixed-method design to characterize AI use guidance offered by member schools of the American Schools and Programs of Public Health. Guidance documents are screened for relevance and accessibility, with the remaining documents being classified as guidelines or policies. The determined policies are analyzed for content via descriptive analysis, content analysis, TF-IDF analysis, and thematic analysis. RESULTS: Out of a possible 155 schools, 18 schools were determined to have a generative AI use policy. TF-IDF analysis identified recurring terms of importance throughout the corpus of policy documents. Content and Thematic Analysis identified areas of focus and themes shared throughout the corpus of documents. The resulting triangulated data are used to identify strengths and shortcomings in the extant policies with suggestions for further development. CONCLUSION: The results of the mixed-method design indicate that extant generative AI guidance in schools and programs of public health in the United States is in its relative infancy. Shared themes and areas of focus show a predominant focus on the intersection of academic integrity and AI use among students and faculty. Additionally, data privacy and security, research ethics, and other areas are currently under consideration. This study demonstrates that AI use governance is growing but narrow in scope. Further development in the areas of pedagogy, legal guidance, and ethical use frameworks are needed in order to meet the growing demand to integrate generative AI into US higher education.

APA Citation

Joshi, Ashish; McGoldrick, Brian; Mittal, Nidhi; Roy, Shongkour; Zeba, Zebunnesa; Ofori, Michael Arthur; Dockery, Stella; Jha, Niharika; Auerbach, John; Cadet, Jean; Kruger, Jessica; Leeman, Robert; Mitchell, Kerry; Molter, Guillaume; Naidech, Andrew; Nezami, Elahe; Orimaye, Sylvester; Queen, Courtney; Shah, Umair; Shaikh, Abdul; Smith, Daniel; Tracy, Melissa; Trapido, Edward; Westermann, Jorg; Wiss, Andrew; Zaccarini, Jonathan; Leshan, Tim E.; Alexander, Linda A.; Atchison, Jamie M.; Ruiz, Eduardo; and Magana, Laura, "Investigating the use of generative AI policies among ASPPH member schools and programs of public health" (2026). GW Authored Works. Paper 9093.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/9093

Department

Health Policy and Management