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  • Summary: Tetlock and Gardner's Superforecasting Summary: The Art and Science of Prediction

  • By: Ant Hive Media
  • Narrated by: Don Moffit
  • Length: 21 mins
  • 4.0 out of 5 stars (2 ratings)
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Summary: Tetlock and Gardner's Superforecasting Summary: The Art and Science of Prediction

By: Ant Hive Media
Narrated by: Don Moffit
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Summary

This is a summary of Tetlock and Gardner's New York Times best seller: Superforecasting: The Art and Science of Prediction

Everyone would benefit from seeing further into the future, whether buying stocks, crafting policy, launching a new product, or simply planning the week's 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 people - including a Brooklyn filmmaker, a retired pipe installer, and a former ballroom dancer - who set out to forecast global events. Some of the volunteers have turned out to be astonishingly good. They've beaten other benchmarks, competitors, and prediction markets. They've 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 Laden's 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 doesn't require powerful computers or arcane methods.

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