lie detection




The Intelligence Advanced Research Projects Activity (IARPA), within the Office of the Director of National Intelligence (ODNI), announced the other day the winner of its first public challenge contest, Investigating Novel Statistical Techniques to Identify Neurophysiological Correlates of Trustworthiness (INSTINCT). The winning solution, JEDI MIND — Joint Estimation of Deception Intent via Multisource Integration of Neuropsychological Discriminators — uses a combination of innovative statistical techniques to improve predictions approximately 15 percent over the baseline analysis.

Date of publication: 
Sun, 29/09/2013
The authors report a meta-analysis of individual differences in detecting deception, confining attention to occasions when people judge strangers’ veracity in real-time with no special aids. The authors have developed a statistical technique to correct nominal individual differences for differences introduced by random measurement error. Although researchers have suggested that people differ in the ability to detect lies, psychometric analyses of 247 samples reveal that these ability differences are minute. In terms of the percentage of lies detected, measurement-corrected standard deviations in judge ability are less than 1%. In accuracy, judges range no more widely than would be expected by chance, and the best judges are no more accurate than a stochastic mechanism would produce.