Words or numbers? Communicating probability in intelligence analysis
Article
Dhami, M. and Mandel, D.R. 2021. Words or numbers? Communicating probability in intelligence analysis. American Psychologist. 76 (3), pp. 549-560. https://doi.org/10.1037/amp0000637
Type | Article |
---|---|
Title | Words or numbers? Communicating probability in intelligence analysis |
Authors | Dhami, M. and Mandel, D.R. |
Abstract | Intelligence analysis is fundamentally an exercise in expert judgment made under conditions of uncertainty. These judgments are used to inform consequential decisions. Following the major intelligence failure that led to the 2003 war in Iraq, intelligence organizations implemented policies for communicating probability in their assessments. Virtually all chose to convey probability using standardized linguistic lexicons in which an ordered set of select probability terms (e.g., highly likely) is associated with numeric ranges (e.g., 80-90%). We review the benefits and drawbacks of this approach, drawing on psychological research on probability communication and studies that have examined the effectiveness of standardized lexicons. We further discuss how numeric probabilities can overcome many of the shortcomings of linguistic probabilities. Numeric probabilities are not without drawbacks (e.g., they are more difficult to elicit and may be misunderstood by receivers with poor numeracy). However, these drawbacks can be ameliorated with training and practice, whereas the pitfalls of linguistic probabilities are endemic to the approach. We propose that, on balance, the benefits of using numeric probabilities outweigh their drawbacks. Given the enormous costs associated with intelligence failure, the intelligence community should reconsider its reliance on using linguistic probabilities to convey probability in intelligence assessments. Our discussion also has implications for probability communication in other domains such as climate science. |
Keywords | subjective probability; uncertainty; verbal probabilities; policy-making; intelligence analysis |
Publisher | American Psychological Association (APA) |
Journal | American Psychologist |
ISSN | 0003-066X |
Electronic | 1935-990X |
Publication dates | |
Online | 23 Jul 2020 |
30 Apr 2021 | |
Publication process dates | |
Deposited | 14 Apr 2020 |
Accepted | 24 Mar 2020 |
Output status | Published |
Accepted author manuscript | |
Copyright Statement | ©American Psychological Association, 2020. This paper is not the copy of record and may not exactly replicate the authoritative document published in the APA journal. Please do not copy or cite without author's permission. The final article is available, upon publication, at: https://doi.org/10.1037/amp0000637 |
Digital Object Identifier (DOI) | https://doi.org/10.1037/amp0000637 |
Web of Science identifier | WOS:000661086200011 |
Language | English |
https://repository.mdx.ac.uk/item/88xz2
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