The study discussed in this working paper explored the perspectives of 13 public health professionals and researchers working across Canadian universities, regional and national public health agencies, professional associations, knowledge translation hubs and international governance bodies to examine their understanding, perceptions and governance needs related to generative artificial intelligence (AI) in public health. Participants shared how they currently understand and use generative AI in public health, identifying both enthusiasm for potential applications (for example, tailoring health messaging, simplifying complex information, streamlining routine tasks) and recognizing that organizational uptake and oversight are still limited. They also highlighted perceived risks of generative AI, including threats to public trust, the rapid spread of misinformation, equity concerns tied to biased training data, and the absence of clear governance, policies and workforce readiness to responsibly use generative AI. Discussions extended to strategic opportunities and enablers, such as avoiding late adoption, leveraging generative AI at the population health level, addressing digital divides, investing in shared infrastructure, creating “bridging” roles between technical and public health sectors, and ensuring tools are customizable to local contexts. Participants stressed the need for reflexive governance and ongoing accountability, calling for continuous monitoring, community involvement and sector-specific frameworks that evolve alongside generative AI technologies to ensure the responsible and equitable integration in public health practice.
