Assessing Uncertainty in Intelligence

Richard Zeckhauser and Jeffrey Allan Friedman

Scholarly Articles from Harvard Kennedy School of Government

Abstract: This article addresses the challenge of managing uncertainty when producing estimative intelligence. Much of the theory and practice of estimative intelligence aims to eliminate or reduce uncertainty, but this is often impossible or infeasible. This article instead argues that the goal of estimative intelligence should be to assess uncertainty. By drawing on a body of nearly 400 declassified National Intelligence Estimates as well as prominent texts on analytic tradecraft, this article argues that current tradecraft methods attempt to eliminate uncertainty in ways that can impede the accuracy, clarity, and utility of estimative intelligence. By contrast, a focus on assessing uncertainty suggests solutions to these problems and provides a promising analytic framework for thinking about estimative intelligence in general.

Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Published in HKS Faculty Research Working Paper Series

Downloads: (external link)
http://dash.harvard.edu/bitstream/handle/1/9359827/RWP12-027_Zeckhauser.pdf (application/pdf)

Related works:
Working Paper: Assessing Uncertainty in Intelligence (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hrv:hksfac:9359827

Access Statistics for this paper

More papers in Scholarly Articles from Harvard Kennedy School of Government Contact information at EDIRC.
Bibliographic data for series maintained by Office for Scholarly Communication ().