Metaculus and Good Judgment Inc Launch First Collaboration

2 min readOct 27, 2022

Good Judgment Inc and Metaculus are pleased to announce our first collaboration. Our organizations, which represent two of the largest human judgment forecasting communities in the world, will compare our results and methodologies in a project comprised of identical forecasting questions that ask about the future of 10 Our World In Data metrics. We plan to share insights, lessons learned, and analysis to contribute to the broader community and to the science of forecasting.

Cohorts of Superforecasters from Good Judgment Inc and Pro Forecasters from Metaculus will make predictions on their separate platforms on a set of 10 questions about technological advances, global development, and social progress on time horizons ranging from one to 100 years.

A Future Fund grant is supporting both organizations in producing these expert forecasts, as well as a public tournament on the Metaculus platform, though this collaboration between Metaculus and GJI is distinct, separate, and voluntary.

“Our shared goal is advancing forecasting as a trusted method for leaders to make critical decisions,” said Gaia Dempsey, CEO of Metaculus. “We’re thrilled to be working with our partners at Good Judgment Inc. This is the first time two of the largest players in the field of forecasting have come together in the spirit of collaboration to compare methodologies and to advance the science of forecasting.”

“We’re excited to be partnering with Metaculus to combine our approaches to apply probabilistic thinking to an uncertain future and help individuals and organizations make better decisions about the future,” said Warren Hatch, Good Judgment’s CEO. “We look forward to building on this collaboration for Our World In Data.”

Good Judgment Inc harnesses the wisdom of the crowd, led by Superforecasters, to quantify hard-to-measure risks for smarter strategic decisions for the private and public sectors.

Metaculus is a forecasting technology platform that optimally aggregates quantitative predictions of future events.