Prediction, Automation, and Decision-Making with AI: Risks and Opportunities
January 2026
3 sessions
About the Series
Launching January 2026
Offered in partnership with the Center for Information Technology Policy at Princeton University, this three-part series supports public sector professionals who are responsible for evaluating, procuring, governing, or overseeing AI-enabled systems in government.
From document processing to demand forecasting, governments are adopting automated and predictive systems to streamline internal operations and support decisionmaking. But these tools vary widely in reliability, risk, and fit for purpose. This series offers a clear, practical guide for public professionals to explore together how to determine when new forms of automation, analysis and prediction work and when they don’t and how to tell the difference.
Through real case studies and hands-on frameworks, participants will learn how automation and prediction actually work in government, where they succeed, where they fail, how to evaluate vendor claims, and how jurisdictions around the world are writing rules to govern these systems responsibly.
By the end of the series, participants will be able to distinguish among different types of AI tools, assess risks and benefits, understand global regulatory trends, and design oversight mechanisms that keep human judgment and accountability at the center.
Prediction, Automation, and Decision Making w…How Not to Buy Stupid AI: A Practical Guide to Evaluating AI Products and Tools
Learn evidence-based strategies for evaluating AI vendors and products, identifying red flags, and making smarter procurement decisions grounded in performance, fairness, and accountability
Prediction, Automation, and Decision Making w…Regulating Algorithms: What Governments Around the World Are Doing—and What Public Servants Should know
Explore how governments globally are governing automated systems and how public professionals can translate emerging regulatory approaches into agency policy, contracting, and oversight today.
Prediction, Automation, and Decision Making w…Prediction Isn’t Intelligence: How Predictive Models Really Work in Government
Examine how predictive models differ from other AI tools, why prediction has hard limits in public sector settings, and how misunderstanding those limits can lead to costly or harmful deployments