Long-Range Subjective-Probability Forecasts of Slow-Motion Variables in World Politics: Exploring Limits on Expert Judgment

46 Pages Posted: 7 Mar 2023 Last revised: 1 May 2023

See all articles by Philip Tetlock

Philip Tetlock

University of Pennsylvania

Christopher Karvetski

Good Judgment Inc

Ville Satopää

INSEAD - Technology and Operations Management

Kevin Chen

University of Pennsylvania

Date Written: March 3, 2023

Abstract

Skeptics see long-range geopolitical forecasting as quixotic. A more nuanced view is that although predictability tends to decline over time, its rate of descent is variable. The current study gives geopolitical forecasters a sporting chance by focusing on slow-motion variables with low base rates of change. Analyses of 5, 10 and 25-year cumulative-risk judgments made in 1988 and 1997 revealed: (a) Specialists beat generalists at predicting nuclear proliferation but not shifting nation-state boundaries; (b) Some counterfactual interventions—e.g., Iran gets the bomb before 2022—boosted experts’ edge but others—e.g., nuclear war before 2022—eliminated it; (c) accuracy fell faster on topics where expertise conferred no edge in shorter-range forecasts. To accelerate scientific progress, we propose adversarial collaborations in which clashing schools of thought strike Bayesian reputational bets on divisive issues and use Lakatosian scorecards to incentivize the honoring of bets.

Keywords: expert judgment, long-range forecasting, nuclear proliferation, cumulative risk, adversarial collaboration

Suggested Citation

Tetlock, Philip and Karvetski, Christopher and Satopää, Ville and Chen, Kevin, Long-Range Subjective-Probability Forecasts of Slow-Motion Variables in World Politics: Exploring Limits on Expert Judgment (March 3, 2023). Available at SSRN: https://ssrn.com/abstract=4377599 or http://dx.doi.org/10.2139/ssrn.4377599

Philip Tetlock (Contact Author)

University of Pennsylvania ( email )

Philadelphia, PA 19104
United States

Christopher Karvetski

Good Judgment Inc ( email )

230 Park Ave Rm 1515
New York, NY
United States

Ville Satopää

INSEAD - Technology and Operations Management ( email )

Boulevard de Constance
77 305 Fontainebleau Cedex
France

Kevin Chen

University of Pennsylvania

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