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Forecasting Research Institute
webforecastingresearch.org·forecastingresearch.org/
FRI is a key institutional player in forecasting science; their methods inform how AI safety researchers and policymakers estimate probabilities of AI-related risks and make decisions under deep uncertainty.
Metadata
Importance: 55/100homepage
Summary
The Forecasting Research Institute (FRI) is a nonprofit research organization dedicated to improving the science and practice of forecasting, with applications to high-stakes policy and risk domains. They develop methodologies, run experiments, and collaborate with governments and nonprofits to make predictions more accurate and actionable. Their work has relevance to AI risk assessment and decision-making under uncertainty.
Key Points
- •Conducts empirical research on forecasting methods, including superforecasting, prediction markets, and aggregation techniques.
- •Partners with policymakers and nonprofits to translate forecasting science into practical decision-support tools.
- •Relevant to AI safety through improving risk estimation, scenario planning, and collective intelligence for existential threats.
- •Bridges academic forecasting research and real-world application in governance and high-stakes domains.
- •Contributes to epistemic infrastructure needed for rational responses to emerging technological risks.
Review
The Forecasting Research Institute (FRI) represents an important evolution in predictive methodology, building on the foundational work of Philip Tetlock in establishing rigorous prediction standards. Their approach moves beyond traditional forecasting by emphasizing practical applications and developing novel techniques for addressing complex, long-term challenges. FRI's research strategy concentrates on four key areas: generating high-quality forecasting questions about complex topics, creating methods for resolving seemingly unresolvable questions, testing forecasting techniques across different contexts, and developing tools to support organizational decision-making. This comprehensive approach demonstrates a sophisticated understanding of predictive science's potential to impact critical global issues, with particular relevance to domains like existential risk, biosecurity, and emerging technologies.
Cited by 3 pages
| Page | Type | Quality |
|---|---|---|
| Forecasting Research Institute (FRI) | Organization | 55.0 |
| AI-Augmented Forecasting | Approach | 54.0 |
| ForecastBench | Project | 53.0 |
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Forecasting Research Institute 0 Advancing the science of forecasting for the public good About us We develop forecasting methods to improve decision-making on high-stakes issues. First-generation forecasting research—spearheaded by FRI Chief Scientist Philip Tetlock and coauthors—focused on establishing a rigorous standard for prediction accuracy. The next generation of work aims to channel this approach into real-world relevance. We work with policymakers and nonprofit organizations to design practical forecasting tools, and test them in large experiments. Our research centers on: (1) Producing high-quality forecasting questions about complex, long-run topics; (2) Novel methods for resolving unresolvable questions; (3) Testing the robustness of forecasting techniques across different domains and contexts; and (4) Using forecasting tools to help organizations make better decisions. Our team Work with us Our recent work Forecasting the Economic Effects of AI Read more The Longitudinal Expert AI Panel (LEAP) Read more Existential Risk Persuasion Tournament: First Wave Follow-up Read more Forecasting Biosecurity Risks from LLMs Read more ForecastBench Read more Subscribe for the latest updates on our work Our work is supported by grants from Coefficient Giving and other philanthropic foundations.
Resource ID:
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