INFER is a community of researchers, analysts, and passionate forecasters that inform U.S. Government policymaking by generating signals and early warning about the future of science and technology trends and events.
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Our mission is to build a collective foresight capability that can provide U.S. Government policymakers with an accurate and nuanced rendering of the future.
Some of the critical issues we're forecasting:
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Will the U.S. retain its competitive advantage in AI?
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How will the U.S. tech sector develop over the coming years?
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How will diplomatic relations evolve and impact the global landscape?
Who should be a forecaster?
Professionals in STEM fields and public policy
Current and former government personnel
Academic researchers and professors
University students
Passionate forecasters of all disciplines
We believe every major policy decision by the U.S. Government can be bolstered by leveraging the collective foresight of both the Federal workforce and U.S. and global citizens who support the United States.
INFER Public is designed to generate valuable signals and early warning about the future of critical science and technology trends and events. This is the public portion of INFER and is one of multiple forecasting sites to be operated as part of this program.
INFER is supporting U.S. Government policymakers and is run by the Applied Research Laboratory for Intelligence and Security (ARLIS) at the University of Maryland and Cultivate Labs. Funding has been provided by a grant from Open Philanthropy.
How INFER WorksCatch up on the latest from our blog
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Read more about our forecasting platform and how your participation is critical to increase the “wisdom” of our crowd.
view faqYour forecasts are crucial for making this forecasting platform a success
We need at least 15 minutes a week from you to...
Submit your probabilistic forecasts based on news sources or your own experience;
Share the rationales of your forecasts to give the context for your thinking and upvote the rationales of other forecasts that you agree with; and
When a forecast question is closed, compare your performance with other participants and the consensus to learn where your forecasts can improve.
Participating institutions in our forecasting community
