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Comment: Experts Who Don't Know They Don't Know

机译:评论:不了解的专家

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摘要

Sadly, the conclusion that Green and Armstrong reach-that experts should not be used for predicting conflict outcomes-is not a surprise. Decades ago, Armstrong taught us that expertise beyond a minimal level does not improve judgmental accuracy across a variety of domains (Armstrong 1980). More recently, Tetlock (2005) drove home that point in a study of hundreds of political experts who made thousands of forecasts over many years. Like Green and Armstrong, Tetlock found the expert forecasts to be frequently inaccurate. In support of Armstrong's previous work, Tetlock suggests that avid readers of The New York Times should be able to predict political events as well as highly trained experts. Green and Armstrong also demonstrate that non-professionals mistakenly expect superior performance from experts relative to what they expect from novices. Although it is true that neither novices nor experts were more accurate than chance in eight conflict-prediction tasks, most study participants did not begin with high expectations of the experts in the first place. Participants expected experts to be accurate 45 percent of the time in tasks in which random guessing would yield a success rate of approximately 28 percent. Although these expectations were higher than chance, they are hardly a ringing endorsement for the perceived value of expert forecasters.
机译:令人遗憾的是,格林和阿姆斯特朗所能达到的结论(不应使用专家来预测冲突结果)并不令人惊讶。几十年前,阿姆斯特朗(Armstrong)告诉我们,超出最低限度的专业知识无法提高各个领域的判断准确性(Armstrong 1980)。最近,Tetlock(2005)在对数百名政治专家的研究中指出了这一点,他们多年来做出了数千次预测。像格林和阿姆斯特朗一样,泰特洛克发现专家的预测经常不准确。为了支持阿姆斯特朗的先前工作,特洛克建议《纽约时报》的狂热读者应该能够预测政治事件以及训练有素的专家。格林和阿姆斯特朗还证明,非专业人士错误地期望专家的表现要优于新手。尽管在八个冲突预测任务中,无论是新手还是专家,都比偶然准确,但是,大多数研究参与者起初并没有对专家寄予厚望。参加者希望专家在完成任务时有45%的时间是准确的,其中随机猜测将使成功率达到约28%。尽管这些期望高于偶然性,但对于专家预测者的感知价值来说,它们几乎没有得到认可。

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