Artificial intelligence is rapidly reshaping how public decisions are made. Yet researchers, practitioners, and policymakers working on these issues often do so in isolation, with few chances to learn from one another.
This online seminar series is designed to close that gap. We bring together scholars, policymakers, and practitioners who are tackling the real-world challenges of deploying AI in public policy domains, including criminal justice, public health, safety‑net programs, housing, environmental policy, and more.
This series spotlights work that promises to improve the use and deployment of AI in policy settings—whether through new ideas, practical methods, or evidence from real‑world deployments. Above all, it offers a space for scholars and public leaders to learn from each other and build the shared understanding needed for effective, responsible use of AI in the public interest.
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Investigates how AI-driven disease surveillance alters the practice of epidemiology, the evidentiary standards used by policymakers, and the governance challenges around real-time public health triage.
Offers a legal-theoretical analysis of due process in automated eligibility decisions, proposing new standards for contestability and procedural fairness in high-stakes governmental algorithms.
Discusses the integration of hyperlocal hazard prediction systems with large-scale climate models, and evaluates how governments can responsibly deploy these tools to support vulnerable populations.