Expert Political Judgment

Expert Political Judgment: How Good Is It? How Can We Know? is a 2005 book by Philip E. Tetlock. Philip E. Tetlock is a Canadian-American political science writer, and is currently the Annenberg University Professor at the University of Pennsylvania, where he is cross-appointed at the Wharton School and the School of Arts and Sciences.

Tetlock co-authored the 2016 book Superforecasting: The Art and Science of Prediction. Jason Zweig wrote about the book Superforcasting in the Wall Street Journal: “The most important book on decision making since Daniel Kahneman's Thinking, Fast and Slow.” The Harvard Business Review likened the book Superforecasting: The Art and Science of Prediction to the book How Not to Be Wrong: The Power of Mathematical Thinking by Jordan Ellenberg.

Reviews of Expert Political Judgment: How Good Is It? How Can We Know?

The abstract for the 2008 journal article Review of: Philip E. Tetlock. 2005. Expert Political Judgment: How Good is it? How Can We Know? published in the journal SSRN Electronic Journal indicates:

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The book assaults common sense with evidence. In order to mount his assault on accepted wisdom, Tetlock spends some 238 pages of text explaining his methods and findings, and considering and refuting many alternative explanations, and adds some 75 pages of technical appendices. The downside of this approach is that some readers may find the book too demanding. That would be a pity as his findings are important. Tetlock’s book reports the results of a two-decade long study of expert predictions. He recruited 284 people whose professions included "commenting or offering advice on political and economic trends." He asked them to forecast the probability that various situations would or would not occur, picking areas (geographic and substantive) within and outside their areas of expertise. In addition to eliciting forecasts, Tetlock also asked questions aimed at understanding how the forecasters came to formulate their forecasts, how they dealt with the failure of their forecasts, how they responded to contradictory information, and how they evaluated the probable accuracy of others' theories and predictions. By 2003, he had accumulated 82,361 forecasts, which provided him a database to evaluate. He then evaluated experts' predictions against outcomes, and against various alternate predictions that he derived from simple statistical procedures, from uninformed non-experts, and from well-informed non-experts.

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