Improving intelligence analysis with decision science

Dhami, Mandeep K. and Mandel, David R. and Mellers, Barbara and Tetlock, Philip (2015) Improving intelligence analysis with decision science. Perspectives in Psychological Science .

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Abstract

Intelligence analysis plays a vital role in policy decision making. Key functions of intelligence analysis include accurately forecasting significant events, appropriately characterizing the uncertainties inherent in such forecasts, and effectively communicating those probabilistic forecasts to stakeholders. We review decision research on probabilistic forecasting and uncertainty communication, drawing attention to findings that could be used to reform intelligence processes and contribute to more effective intelligence oversight. We recommend that the intelligence community (IC) regularly and quantitatively monitor its forecasting accuracy to better understand how well it is achieving its functions. We also recommend that the IC use decision science to improve these functions (namely, forecasting and communication of intelligence estimates made under conditions of uncertainty). In the case of forecasting, decision research offers suggestions for improvement that involve interventions on data (e.g., transforming forecasts to debias them) and behavior (e.g., via selection, training, and effective team structuring). In the case of uncertainty communication, the literature suggests that current intelligence procedures, which emphasize the use of verbal probabilities, are ineffective. The IC should, therefore, leverage research that points to ways in which verbal probability use may be improved as
well as exploring the use of numerical probabilities wherever feasible.

Item Type: Article
Research Areas: A. > School of Science and Technology > Psychology > Language, Learning and Cognition group
Item ID: 22734
Depositing User: Mandeep Dhami
Date Deposited: 24 Oct 2017 15:43
Last Modified: 19 Nov 2018 03:18
URI: http://eprints.mdx.ac.uk/id/eprint/22734

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