Generative AI Policies at U.S. Public Health Schools

A collection of 18 generative AI use policies from member schools of the American Schools and Programs of Public Health. The dataset was created by Ashish Joshi through a mixed-method analysis of publicly available documents. It was last updated in April 2026.

Use Cases

• Analyze TF-IDF scores of recurring terms like 'academic integrity' or 'data privacy' across policy documents.
• Identify shared themes from content analysis, such as focus on research ethics or pedagogical frameworks.
• Compare policy scope across the 18 identified schools based on document classification as guidelines or formal policies.

Strengths

• Includes policies from 18 distinct institutions.
• Analysis employs multiple methods: TF-IDF, content analysis, and thematic analysis.
• Documents are screened for relevance and accessibility.

Limitations

• Very small sample size of 18 policies from a potential pool of 155 schools.
• Scope is limited to U.S. public health schools, limiting geographic generalizability.
• Dataset size is 14.5 KB, indicating a limited corpus of primary text data.

Provenance

Source

American Schools and Programs of Public Health (ASPPH) member schools.

Collection Method

Mixed-method design involving screening, classification, and analysis of publicly available guidance documents.

Time Range

Policies collected as of the study date; specific document dates are not provided.

Freshness

Last updated in April 2026.

Geography

United States.