Between approximately 2011 and 2015, a research project sponsored by the Intelligence Advanced Research Projects Activity (IARPA) — the U.S. intelligence community's research-and-development organization — ran one of the largest controlled forecasting tournaments in history.

The Good Judgment Project, led by Philip Tetlock and Barbara Mellers at the University of Pennsylvania, recruited thousands of volunteer forecasters, asked them to assign calibrated probabilities to specific geopolitical questions over multi-month time horizons, scored their performance using Brier scores (a standard measure of probability-forecasting accuracy), and identified a small subset of consistently top-performing forecasters whom the project termed 'superforecasters.' The cumulative findings — documented in Tetlock and Gardner's Superforecasting: The Art and Science of Prediction (Crown, 2015) and in the underlying academic literature — were that careful forecasting practice substantially outperformed unstructured intuition, that top-performing volunteer forecasters substantially outperformed broader populations, and that in some categories the top volunteer forecasters performed comparably to or better than U.S.

intelligence community analysts with classified-information access.