Obstacles to Harnessing Analytic Innovation in Foreign Policy Analysis: A Case Study of Crowdsourcing in the U.S. Intelligence Community

Laura Resnick Samotin (lr2771@columbia.edu), Jeffrey A. Friedman and Michael C. Horowitz
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Laura Resnick Samotin: Unknown
Jeffrey A. Friedman: Unknown
Michael C. Horowitz: Unknown

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Abstract: We conducted interviews with national security professionals to examine 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' ability to generate accurate predictions. Interviewees offered many actionable suggestions for addressing these challenges in future efforts to incorporate crowdsourcing platforms or other algorithmic tools into intelligence tradecraft.

Date: 2023
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Published in Intelligence and National Security, 2023, vol. 38 (n° 4), pp.558-575. ⟨10.1080/02684527.2022.2142352⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04262738

DOI: 10.1080/02684527.2022.2142352

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