How explainable AI and One Health principles can be integrated to combat zoonotic diseases and cross-sector health threats.
Analysis of how AI could transform public health planning—including forecasting and resource allocation—while raising equity concerns.
Perspective on applying machine learning in healthcare: cautions against shortcuts, emphasizes evidence, validation, and equity.
Framework for transforming public health practice with AI, covering core capabilities, governance, and equity-centered implementation.
Analysis of the growing environmental impact of AI data centers' rising energy demands on climate and sustainability goals.
Report on the AI capability gap between advanced AI developers and public health agencies, and strategies to close the divide.
Framework for designing AI evaluations that matter: linking AI system assessment to real-world outcomes and stakeholder needs.
Webinar on AI applications in health policy and systems research, exploring the shift from experimentation to real-world implementation.
Content analysis of social determinants of health accelerator plans using AI/NLP to identify themes and equity gaps at scale.
GenAI-in-healthcare framework with 4 principles: map applications to strengths, define evaluations, balance safety, ensure transparency.
5 steps for public health leaders to use AI responsibly: build awareness, pilot uses, manage risk, invest in staff training.
Guidance on protecting scientific data integrity when using generative AI tools in research and public health contexts.
Blended online course from Digital Bridge giving community health workers foundational AI literacy for public health and service delivery.
HSCC living glossary of healthcare AI terms—governance-ready definitions for clinical, operational, compliance, and technical stakeholders.
Kansas Health Institute template and guidance for public health organizations to develop AI policies tailored to their context.
OpenAI's AI Job Transition Framework: employer and policy recommendations for supporting workers displaced or reshaped by AI.
Critical look at why evaluating AI health interventions is often inadequate and what better evaluation frameworks should require.
CDC success story: using AI to improve public health efficiency and outbreak response readiness through data modernization.
New York City AI Action Plan: strategy for responsible AI use in city government, services, and public engagement.