Literature DB >> 32700939

Words or numbers? Communicating probability in intelligence analysis.

Mandeep K Dhami1, David R Mandel2.   

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. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Year:  2020        PMID: 32700939     DOI: 10.1037/amp0000637

Source DB:  PubMed          Journal:  Am Psychol        ISSN: 0003-066X


  2 in total

1.  Verbal Descriptions of the Probability of Treatment Complications Lead to High Variability in Risk Perceptions: A Survey Study.

Authors:  Joshua E Rosen; Nidhi Agrawal; David R Flum; Joshua M Liao
Journal:  Ann Surg       Date:  2021-10-25       Impact factor: 13.787

2.  On measuring agreement with numerically bounded linguistic probability schemes: A re-analysis of data from Wintle, Fraser, Wills, Nicholson, and Fidler (2019).

Authors:  David R Mandel; Daniel Irwin
Journal:  PLoS One       Date:  2021-03-18       Impact factor: 3.240

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.