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Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament

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  • Karger, Ezra
  • Rosenberg, Josh
  • Jacobs, Zachary
  • Hickman, Molly
  • Tetlock, Phillip E.

Abstract

A multi-stage persuasion-forecasting tournament asked specialists and generalists (“superforecasters”) to explain their probability judgments of short- and long-run existential threats to humanity. Specialists were more pessimistic, especially on long-run threats posed by artificial intelligence (AI). Despite incentives to share their best arguments during four months of discussion, neither side materially moved the other’s views. This would be puzzling if participants were Bayesian agents methodically sifting through elusive clues about distant futures but it is less puzzling if participants were boundedly rational agents searching for confirmatory evidence as the risks of embarrassing accuracy feedback receded. Consistent with the latter mechanism, strong AI-risk proponents made particularly extreme long- but not short-range forecasts and over-estimated the long-range AI-risk forecasts of others. We stress the potential of these methods to inform high-stakes debates, but we acknowledge limits on what even skilled forecasters can achieve in anticipating rare or unprecedented events.

Suggested Citation

  • Karger, Ezra & Rosenberg, Josh & Jacobs, Zachary & Hickman, Molly & Tetlock, Phillip E., 2025. "Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament," International Journal of Forecasting, Elsevier, vol. 41(2), pages 499-516.
  • Handle: RePEc:eee:intfor:v:41:y:2025:i:2:p:499-516
    DOI: 10.1016/j.ijforecast.2024.11.008
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    References listed on IDEAS

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    1. Nick Bostrom, 2019. "The Vulnerable World Hypothesis," Global Policy, London School of Economics and Political Science, vol. 10(4), pages 455-476, November.
    2. Yaniv, Ilan & Kleinberger, Eli, 2000. "Advice Taking in Decision Making: Egocentric Discounting and Reputation Formation," Organizational Behavior and Human Decision Processes, Elsevier, vol. 83(2), pages 260-281, November.
    3. Dražen Prelec & H. Sebastian Seung & John McCoy, 2017. "A solution to the single-question crowd wisdom problem," Nature, Nature, vol. 541(7638), pages 532-535, January.
    4. Rowe, Gene & Wright, George, 1999. "The Delphi technique as a forecasting tool: issues and analysis," International Journal of Forecasting, Elsevier, vol. 15(4), pages 353-375, October.
    5. Victor Richmond R. Jose & Robert L. Winkler, 2009. "Evaluating Quantile Assessments," Operations Research, INFORMS, vol. 57(5), pages 1287-1297, October.
    6. Scott E. Page, 2007. "Prologue to The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies," Introductory Chapters, in: The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies, Princeton University Press.
    7. Bonaccio, Silvia & Dalal, Reeshad S., 2006. "Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences," Organizational Behavior and Human Decision Processes, Elsevier, vol. 101(2), pages 127-151, November.
    Full references (including those not matched with items on IDEAS)

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