How can state-of-the-art probabilistic forecasting tools be used to advance expert debates on big policy questions? Using Foretell, a crowd forecasting platform piloted by CSET, we trialed a method to break down a big question—”What is the future of the DOD-Silicon Valley relationship?”—into measurable components, and then leveraged the wisdom of the crowd to reduce uncertainty and arbitrate disagreement among a group of experts.

CSET Research Fellow Michael Page and Director of Data Science Catherine Aiken discussed how crowd forecasting methods can help to better understand tricky policy questions.

Foretell's crowd forecasting can help predict the market of China's politics.

Foretell, a project run by the Center for Security and Emerging Technology (CSET) at Georgetown University, which also uses the Cultivate platform, employs this methodology to predict the course of technological competition between America and China.

Foretell was CSET's crowd forecasting pilot project focused on technology and security policy. It connected historical and forecast data on near-term events with the big-picture questions that are most relevant to policymakers. In January 2022, Foretell became part of a larger forecasting program to support U.S. government policy decisions called INFER, which is run by the Applied Research Laboratory for Intelligence and Security at the University of Maryland and Cultivate Labs.

Axios Future previewed CSET's Issue Brief, "Future Indices," on using historical data and the wisdom of the crowd to predict future trends.

Foretell was CSET's crowd forecasting pilot project focused on technology and security policy. It connected historical and forecast data on near-term events with the big-picture questions that are most relevant to policymakers. In January 2022, Foretell became part of a larger forecasting program to support U.S. government policy decisions called INFER, which is run by the Applied Research Laboratory for Intelligence and Security at the University of Maryland and Cultivate Labs. This issue brief used recent forecast data to illustrate Foretell’s methodology.