Rethinking the training of intelligence analysts

被引:23
|
作者
Chang, Welton [1 ,2 ,3 ]
Tetlock, Philip E. [4 ,5 ,6 ]
机构
[1] Univ Penn, Philadelphia, PA 19104 USA
[2] US Army, Ft Belvoir, VA 22060 USA
[3] Def Intelligence Agcy, Washington, DC 20340 USA
[4] Univ Penn, Psychol, Philadelphia, PA 19104 USA
[5] Univ Penn, Wharton Sch, Philadelphia, PA 19104 USA
[6] Univ Penn, Polit Sci, Philadelphia, PA 19104 USA
关键词
ERROR MANAGEMENT THEORY; DECISION-MAKING; ACCURACY; UNDERCONFIDENCE; EVOLUTION; OVERCONFIDENCE; PSYCHOLOGY; FREQUENCY; FORECASTS; BIASES;
D O I
10.1080/02684527.2016.1147164
中图分类号
K [历史、地理];
学科分类号
06 ;
摘要
Despite intense scrutiny and promised fixes resulting from intelligence 'transformation' efforts, erroneous analytic assessments persist and continue to dominate news coverage of the US intelligence community. Existing analytic training teaches analysts about common cognitive biases and then aims to correct them with structured analytic techniques. On its face, this approach is eminently reasonable; on close inspection, incomplete and imbalanced. Current training is anchored in a mid-twentieth century understanding of psychology that focuses on checking over-confidence and rigidity but ignores the problems of under-confidence and excessive volatility. Moreover it has never been validated against objective benchmarks of good judgment. We propose a new approach: (a) adopting scientifically validated content and regularly testing training to avoid institutionalizing new dogmas; (b) incentivizing analysts to view training guidelines as means to the end of improved accuracy, not an end in itself.
引用
收藏
页码:903 / 920
页数:18
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