Correcting Judgment Correctives in National Security Intelligence

Abstract

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Intelligence analysts, like other professionals, form norms that define standards of tradecraft excellence. These norms, however, have evolved in an idiosyncratic manner that reflects the influence of prominent insiders who had keen psychological insights but little appreciation for how to translate those insights into testable hypotheses. The net result is that the prevailing tradecraft norms of best practice are only loosely grounded in the science of judgment and decision-making. The “common sense” of prestigious opinion leaders inside the intelligence community has pre-empted systematic validity testing of the training techniques and judgment aids endorsed by those opinion leaders. Drawing on the scientific literature, we advance hypotheses about how current best practices could well be reducing rather than increasing the quality of analytic products. One set of hypotheses pertain to the failure of tradecraft training to recognize the most basic threat to accuracy: measurement error in the interpretation of the same data and in the communication of interpretations. Another set of hypotheses focuses on the insensitivity of tradecraft training to the risk that issuing broad-brush, one-directional warnings against bias (e.g., over-confidence) will be less likely to encourage self-critical, deliberative cognition than simple response-threshold shifting that yields the mirror-image bias (e.g., under-confidence). Given the magnitude of the consequences of better and worse intelligence analysis flowing to policy-makers, we see a compelling case for greater funding of efforts to test what actually works.

Keywords

• judgment and decision making
• intelligence analysis
• debiasing
• error management
• corrective action
• organizational policies