Assessing Uncertainty in Intelligence

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. ACKNOWLEDGMENTS

Towards an evidence-based approach to communicating uncertainty in intelligence analysis

“…4 Linguistic probabilities may be preferred because people find it is easier and more natural to use language rather than numbers, and because linguistic probabilities allow expression of judgment uncertainty. 5 Friedman and Zeckhauser (2012) found that US intelligence analysts used . Towards an evidence-based approach to communicating uncertainty in intelligence analysis.…”

The Theoretical and Empirical Approaches to Uncertainty and Conflict in International Relations

“…Rathbun (2007) situates a discussion of uncertainty in terms of the IR paradigms. Friedman and Zeckhauser (2012) and Friedman and Zeckhauser (2015) emphasize uncertainty in the realm of intelligence. How does greater precision in intelligence estimates affect interpretability and accuracy?…”

Desirable attributes of an effective intelligence analyst

“…It is possible that some data contain informative value but do not seem interesting or usable at that point, so they may be ignored, i.e. the necessary attention may not be paid to them (16). A special problem is the possibility to fabricate data and place them intentionally in order to create confusion and make taking an objective view on some event or phenomenon more difficult.…”