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Superforecasting: the art and science of prediction
Abstract
A New York Times Bestseller An Economist Best Book of 2015 most important book on decision making since Daniel Kahneman's Thinking, Fast and Slow. Jason Zweig, The Wall Street Journal Everyone would benefit from seeing further into the future, whether buying stocks, crafting policy, launching a new product, or simply planning the weeks meals. Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight, and Tetlock has spent the past decade trying to figure out why. What makes some people so good? And can this talent be taught? In Superforecasting, Tetlock and coauthor Dan Gardner offer a masterwork on prediction, drawing on decades of research and the results of a massive, government-funded forecasting tournament. The Good Judgment Project involves tens of thousands of ordinary peopleincluding a Brooklyn filmmaker, a retired pipe installer, and a former ballroom dancerwho set out to forecast global events. Some of the volunteers have turned out to be astonishingly good. Theyve beaten other benchmarks, competitors, and prediction markets. Theyve even beaten the collective judgment of intelligence analysts with access to classified information. They are superforecasters. In this groundbreaking and accessible book, Tetlock and Gardner show us how we can learn from this elite group. Weaving together stories of forecasting successes (the raid on Osama bin Ladens compound) and failures (the Bay of Pigs) and interviews with a range of high-level decision makers, from David Petraeus to Robert Rubin, they show that good forecasting doesnt require powerful computers or arcane methods. It involves gathering evidence from a variety of sources, thinking probabilistically, working in teams, keeping score, and being willing to admit error and change course. Superforecasting offers the first demonstrably effective way to improve our ability to predict the futurewhether in business, finance, politics, international affairs, or daily lifeand is destined to become a modern classic.
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Cited by
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Hemming, V., Burgman, M. A., Hanea, A. M., McBride, M. F., & Wintle, B. C. (2018) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.12857 · Cited by 528
Understanding algorithm aversion: When is advice from automation discounted?
Prahl, A., & Van Swol, L. (2017) · Journal of Forecasting · doi:10.1002/for.2464 · Cited by 308
Modelling complex systems of heterogeneous agents to better design sustainability transitions policy
Mercure, J.-F., Pollitt, H., Bassi, A. M., Viñuales, J. E., & Edwards, N. R. (2016) · Global Environmental Change · doi:10.1016/j.gloenvcha.2016.02.003 · Cited by 204
The feeling of grip: novelty, error dynamics, and the predictive brain
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“Improving Intelligence Analysis with Decision Science.”
Dhami, M. K., Mandel, D. R., Mellers, B. A., & Tetlock, P. E. (2015) · Perspectives on Psychological Science · doi:10.1177/1745691615598511 · Cited by 104
Metadata
- Venue
- Choice Reviews Online
- Publisher
- American Library Association
- Published
- 2016-04-19
- Volume
- 53
- Issue
- 09
- Pages
- 53-4021-53-4021
- ISSN
- 0009-4978 (ISSN-L)
- 1523-8253
- OpenAlex
- W2160554939
- Cited by
- 919
- References
- 0
- Type
- book review
- Language
- en
- Open access
- closed
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