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The Forecasting Research Institute (FRI) was founded in late 2022 by a team that includes Philip Tetlock · the Penn professor renowned for his work on superforecasting and the Good Judgment Project · alongside CEO Josh Rosenberg (formerly a Senior Advisor at GiveWell) and a team of researchers with backgrounds in economics, behavioral science, statistics, and public health. FRI is a 501(c)(3) nonprofit registered in Delaware and operates with roughly 15-20 staff plus a network of scientific advisors and part-time collaborators.
FRI's work is organized around two complementary tracks: foundational forecasting science and applied translational research. On the foundational side, the organization studies how to produce accurate predictions about complex, long-horizon topics · including low-probability catastrophes · and develops novel resolution methods for questions that cannot be resolved through direct observation alone. On the applied side, FRI works to make these tools actionable for organizations and policymakers…
FRI believes that better calibrated, quantitative forecasts about catastrophic and existential risks will improve decision-making by policymakers, philanthropists, and the broader EA community. By producing rigorous probability estimates on AI risk, nuclear risk, and biosecurity threats · and by developing the scientific methods to make such forecasts reliable · FRI creates a more accurate empirical foundation for prioritizing and funding interventions. If key decision-makers have better-calibrated uncertainty about tail risks, they can allocate resources more rationally, respond to early warning signals earlier, and avoid both over- and under-reaction to speculative threats. FRI also works to identify sources of disagreement among experts, which can surface crux questions that · if answered · would most change the field's collective beliefs about existential risk.
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View on grantmaking.aiA three-year project led by the Forecasting Research Institute and academic partners that collects monthly probabilistic forecasts from AI experts, industry professionals, policy researchers, economists, and the public on AI capabilities, labor-market impacts, and other economic and societal consequences of AI.
A dynamic, continuously updated benchmark developed and maintained by the Forecasting Research Institute to evaluate large language models’ forecasting accuracy on automatically generated time-series questions and prediction-market questions, comparing model performance to human superforecasters and the general public.
An expert elicitation study by the Forecasting Research Institute that surveys 46 biosecurity and biology experts and 22 superforecasters to estimate how frontier large language models could affect biosecurity risks and how safeguards like DNA screening and AI safety measures might mitigate those risks.
A 2022 forecasting tournament run by the Forecasting Research Institute that brought together 169 superforecasters and domain experts in a multi-stage deliberative process to generate high-quality long-run forecasts about existential and catastrophic risks from AI, pandemics, nuclear war, climate change, and other global threats.