Research Findings

Getting to the truth

Science and myths about lie detection

We are now at a tipping point in the field of lie and truth detection. Peer-reviewed research and high-stake applications are showing that we need two main skillsets to perform better than the average human and the polygraph: 1) recognizing deceptive behavior via multi-channel analysis and 2) using unexpected prompts in interviews to elicit truth.

In this column, I’ll steer you away from the myths and toward the science and hard evidence in recognizing truth, reading emotions and detecting deception during interviews. I’ll avoid snake-oil claims and approaches that only use one or two elements to detect deception, such as “cognitive load,” facial expressions, body language, verbal content, voice and reliance on biometrics, such as polygraphs.

Investigators who depend on just a few of these approaches might yield risky and unreliable results (Porter and ten Brinke, 2010:69). I encourage you to employ a multi-channel, corroborative approach to help you make reliable decisions (Pearse and Lansley, 2010).

In the “Research Findings” column of the March/April 2019 issue of Fraud Magazine, Vincent Denault, CFE, and Louise Marie Jupe reminded us that that distinguishing “unsubstantiated claims from those that are evidence-based … isn’t always an easy task.” I agree with them.

I’d go a step further and argue that the evidence from some peer-reviewed, deception-detection research is based on dubious experiments involving students completing exercises with low-stake threats.

Those who are interested in discovering high-stakes lies note that many research experiments’ deceptions are trivial (Ekman, 2009). Lies are generally labeled “high stake” when the subject could experience large positive consequences of getting away with the lie (such as money, power, freedom) or large negative consequences of getting caught (death, incarceration, money loss).

And those who are interested in deceptive interactions tend to denounce research outcomes about lies, which result from an artificial, experimental context (Buller and Burgoon, 1996).

Our clients include company owners, bank officials, due-diligence investigators (often engaged by investors/brokers), military organizations, counterintelligence and anti-terrorism agents, and law enforcement officers. The stakes can be life-or-death situations, national security breaches and millions of dollars. We dare not train these professionals to judge lies or truth in their contexts using research findings in which stakes are low — peer reviewed or not. The approaches we use work well when the stakes are high but are less reliable for low-stake contexts (Archer and Lansley).

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