Obstacles to harnessing analytic innovations in foreign policy analysis: a case study of crowdsourcing in the U.S. intelligence community

被引:0
|
作者
Samotin, Laura Resnick [1 ,2 ]
Friedman, Jeffrey A. [3 ]
Horowitz, Michael C. [4 ,5 ]
机构
[1] Columbia Univ, Sch Int & Publ Affairs, Int Relat, New York, NY 10027 USA
[2] Columbia Univ, Sch Int & Publ Affairs, Strateg Partnerships, New York, NY 10027 USA
[3] Dartmouth Coll, Govt, Hanover, NH USA
[4] Univ Penn, Perry World House, Philadelphia, PA USA
[5] Univ Penn, Philadelphia, PA USA
关键词
RISK; TECHNOLOGY; ACCURACY;
D O I
10.1080/02684527.2022.2142352
中图分类号
K [历史、地理];
学科分类号
06 ;
摘要
We interviewed national security professionals to understand why the U.S. Intelligence Community has not systematically incorporated prediction markets or prediction polls into its intelligence reporting. This behavior is surprising since crowdsourcing platforms often generate more accurate predictions than traditional forms of intelligence analysis. Our interviews suggest that three principal barriers to adopting these platforms involved (i) bureaucratic politics, (ii) decision-makers lacking interest in probability estimates, and (iii) lack of knowledge about these platforms' capabilities. Interviewees offered many actionable suggestions for addressing these challenges in future efforts to incorporate crowdsourcing platforms or other algorithmic tools into intelligence tradecraft.
引用
收藏
页码:558 / 575
页数:18
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