Do Lie Detection Tools Really Catch Liars?

Lying is ubiquitous in every society. However, in forensic contexts lies must be revealed so that investigations/judgments can be fair and effective. Objective: For this reason, distinct tools (verbal and nonverbal) of lie detection were examined. Method: this study presents a non-systematic qualitative review of the main techniques of lie detection and credibility assessment, dividing them into verbal and nonverbal approaches. Results: CBCA and RM showed the best performance in distinguishing between truth and lie within verbal tools. Lack of empirical support made SCAN not recommended for lie detection applications. Moreover, studies have shown that people guided by BAI are less accurate in detecting lies than untrained people. Ekman’s Deception Theory (EDT) showed more effective predictions about nonverbal deception cues than BAI. However, the lack of standardization in the use of EDT predictions to detect lies can be seen as a weakness of the method. Conclusion: Future efforts may be aimed at developing a tool that uses both verbal and nonverbal predictions to obtain greater accuracy in detecting lies than currently available methods.