FFC/2025: The 26th Federal Forecasters Conference
Thursday, October 9, 2025
9:00 am - 4:30 pm
Event Details
- Date: Thursday, October 9, 2025
- Location: Elliott School of International Affairs, The George Washington University, Washington, DC
- Program information coming soon!
- Registration here. Note that the virtual option is for the morning sessions only.
- Forecasting Contest Official Entry Form. Entries are due on September 16 @ 11:59 pm EDT (UTC-4)
Conference Theme: Risks and Opportunities of AI and ML in Forecasting
Forecasters rely increasingly on AI and machine learning to navigate rapidly evolving environments with complex and uncertain events. From global pandemics and geopolitical conflicts to shifting trade dynamics, economic crises, and natural disasters, these events present both challenges and opportunities for forecasting. AI and machine learning offer powerful tools to enhance predictive accuracy, identify emerging trends, and integrate vast and unconventional data sources. However, they also may introduce new risks, biases, and difficulties in the interpretability of the results. The 2025 Federal Forecasters Conference will explore how forecasters are leveraging AI and machine learning to improve forecasting in dynamic, rapidly changing environments. Can these methodologies decrease forecast errors and enhance decision- making? What best practices ensure transparency, reliability, and replicability for AI-driven forecasts? How can AI-generated insights be effectively communicated to policymakers?
Plenary Speakers
TBA
Sponsoring Agencies
Bureau of Economic Analysis • Bureau of Labor Statistics • Congressional Budget Office • Department of Veterans Affairs • Economic Research Service, USDA • Federal Energy Regulatory Commission • Federal Reserve Board • Internal Revenue Service • Office of Economic Policy, U.S. Department of the Treasury • U.S. Census Bureau • U.S. Department of Labor • U.S. Energy Information Administration, Office of Energy Analysis • U.S. Geological Survey
Partnering Organizations
The George Washington University: H.O. Stekler Research Program on Forecasting, AI Economics Program, Department of Economics, and Institute for International Economic Policy, Elliott School of International Affairs
Society of Government Economists
Center for Financial Stability