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The Role of Generative AI in Public Health Advocacy: Two Case Studies for Eating Disorders Policy
Stanley Huang1,2,3, Chuying Huo1,4, Jill R Kavanaugh1,3
1Strategic Training Initiative for the Prevention of Eating Disorders, Boston, Massachusetts, USA.
Objective:
This Spotlight article explores opportunities for the use of generative artificial intelligence (AI) to support real-world eating disorders (ED) prevention policy advocacy campaigns.
Method:
Through two case studies, we illustrate ongoing applications of generative AI to enhance core activities to drive public health policy advocacy campaigns. Case Study 1 describes an interactive, sociotechnical system that trains community advocates for effective legislative advocacy. Case Study 2 discusses an online chatbot that supports legal research into statute, case law, and proposed legislation.
Results:
Generative AI can power applications that can scale public health policy advocacy training and improve understanding of legal contexts. When deployed properly, they can reduce time spent on manual legal research and enhance policy advocacy skills and strategy.
Discussion:
Generative AI offers practical solutions for strengthening community-based public health policy advocacy. When integrated with established public health advocacy frameworks, these tools can help advocacy teams scale training efforts and garner strategic insights for robust advocacy campaigns.
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