Prof. Philip Tetlock's Forecasting Research – Founders Pledge
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This Founders Pledge research page profiles Philip Tetlock's forecasting work and its application to existential and global catastrophic risks, including AI, engineered pandemics, and nuclear threats, explaining how second-generation forecasting tournaments could improve early-warning systems for AI safety and other x-risks.
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Summary
Founders Pledge profiles Philip Tetlock's research on improving probabilistic forecasting for global catastrophic and existential risks. The work builds on first-generation forecasting tournament successes (superforecasters, training, teamwork, weighted algorithms) to develop second-generation methods that identify early-warning indicators, craft policy-relevant explanations, and amplify high-value contributors. These techniques aim to produce calibrated risk assessments for unprecedented threats like engineered pandemics and superintelligent AI.
Key Points
- •Tetlock's first-generation forecasting tournaments (IARPA 2011-15) demonstrated that superforecaster identification, training, teamwork, and weighted averaging all beat unweighted crowd forecasts.
- •Second-generation tournaments aim to identify early-warning indicators of x-risks in noisy environments and translate them into actionable policy insights.
- •Forecasting methods could help prioritize interventions against unprecedented risks like engineered pandemics and superintelligent AI by producing calibrated probability estimates.
- •Even short-term forecasting (under 5 years) remains valuable as an early-warning system for long-run existential risks.
- •Founders Pledge funded a paper by Tetlock et al. on 'Improving Judgments of Existential Risks' outlining key challenges and proposed solutions.
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Related research
Safeguarding the future report
Learn more Philip E. Tetlock is a Penn Integrates Knowledge (PIK) Professor at the University of Pennsylvania, cross-appointed in the School of Arts and Sciences and Wharton. This research focuses on improving probability estimates of early-warning indicators of global catastrophic and existential risks.
What problem are they trying to solve?
Professor Tetlock’s research could be valuable for anticipating and mitigating global catastrophic risks, for example, those caused by natural or engineered pathogens, artificial intelligence, nuclear weapons or extreme climate change. To do this, Tetlock and collaborators are combining traditional techniques proven effective in first-generation forecasting tournaments with more experimental methods to build a discipline of second-generation forecasting.
Accurately forecasting future events is extremely challenging in itself but Tetlock’s research has previously developed methods to improve forecasting accuracy. Figure 1 shows that in the IARPA geopolitical tournaments of 2011-15: (a) unweighted averaging of regular forecasters improved accuracy well above chance; (b) Tetlock’s research team developed four methods of beating unweighted averaging - by spotting “superforecasting” talent, training, teamwork, and weighted averaging algorithms. 1
Figure 1
Source: Good Judgment . 2
In a recent paper funded by Founders Pledge, Improving Judgments of Existential Risks: Better Forecasts, Questions, Explanations, Policies , Tetlock and collaborators lay out their vision of key challenges and solutions for improving judgments of existential risks.
Tetlock notes that traditional tournaments can help in part by “chart[ing] the ebb and flow of judgments of short-run potential precursors of long-run X-risks.” But problems remain: how do we accurately identify these precursors, and how does early warning lead to risk mitigation? To address these and other challenges, Tetlock’s second generation of tournaments seeks to do three things that first-generation tournaments fail to do:
“identify early-warning indicators in a noisy, distraction-laden world;”
“craft insightful explanations that assist policymakers in spotting lead indicators;”
“give louder voices in policy debates to high-value contributors at each phase of the knowledge-production cycle.”
In their recent paper, Tetlock and colleagues address these challenges and broader objections. Tetlock hypothesizes that “across a surprising range of environments, X-risk tournaments are good bets to deliver value even with moderately myopic forecasters".
What do they do?
Over the last 35 years, Professor Tetlock has pioneered the practice of forecasting, a way to make predictions about future events more accurate and useful. Professor Tetlock has been described by the economist Tyler Cowen as “one of the greatest social scientists in the world” 3 and his papers have garnered over 55,000 citat
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