Lie, truth, lie: the role of task switching in a deception context

Detecting lies in investigative interviews through the analysis of response latencies and error rates to unexpected questions

In this study, we propose an approach to detect deception during investigative interviews by integrating response latency and error analysis with the unexpected question technique. Sixty participants were assigned to an honest (n = 30) or deceptive group (n = 30). The deceptive group was instructed to memorize the false biographical details of a fictitious identity. Throughout the interviews, participants were presented with a randomized sequence of control, expected, and unexpected open-ended questions about identity. Responses were audio recorded for detailed examination. Our findings indicate that deceptive participants showed markedly longer latencies and higher error rates when answering expected (requiring deception) and unexpected questions (for which premeditated deception was not possible). Longer response latencies were also observed in participants attempting deception when answering control questions (which necessitated truthful answers). Moreover, a within-subject analysis highlighted that responding to unexpected questions significantly impaired individuals' performance compared to answering control and expected questions. Leveraging machine-learning algorithms, our approach attained a classification accuracy of 98% in distinguishing deceptive and honest participants. Additionally, a classification analysis on single response levels was conducted. Our findings underscore the effectiveness of merging response latency metrics and error rates with unexpected questioning as a robust method for identity deception detection in investigative interviews. We also discuss significant implications for enhancing interview strategies.

Are Intelligent People Better Liars? Relationships between Cognitive Abilities and Credible Lying

Lying is essential to social communication. Despite years of research, its detection still poses many challenges. This is partly because some individuals are perceived as truthful and reliable, even when lying. However, relatively little is known about these effective liars. In our study, we focused on the cognitive functioning of effective liars. We tested 400 participants who completed tasks measuring executive functions, verbal fluency, and fluid intelligence, and also made four statements (two true and two false, half of them written and half oral). The reliability of the statements was then assessed. Only fluid intelligence was found to be relevant for reliable lying. This relationship was only evident for oral statements, suggesting that the importance of intelligence is highlighted when statements are made spontaneously without prior preparation.

The Role of Cognition in Dishonest Behavior

Dishonesty has received increased attention from many professionals in recent years for its relevance in many social areas such as finance and psychology, among others. Understanding the mechanisms underlying dishonesty and the channels in which dishonesty operates could enable the detection and even prevention of dishonest behavior. However, the study of dishonesty is a challenging endeavor; dishonesty is a complex behavior because it imposes a psychological and cognitive burden. The study of this burden has fostered a new research trend that focuses on cognition’s role in dishonesty. This paper reviews the theoretical aspects of how such cognitive processes modulate dishonest behavior. We will pay special attention to executive functions such as inhibitory processes, working memory, or set-shifting that may modulate the decision to be (dis)honest. We also account for some frameworks in cognitive and social psychology that may help understand dishonesty, such as the Theory of Mind, the role of creative processes, and discourse analyses within language studies. Finally, we will discuss some specific cognitive-based models that integrate cognitive mechanisms to explain dishonesty. We show that cognition and dishonest behavior are firmly related and that there are several important milestones to reach in the future to advance the understanding of dishonesty in our society.

Delta plots do not reveal response inhibition in lying

The role of response inhibition in lying is debated. By using the delta-plot method applied to the Sheffield Lie Test, Debey, Ridderinkhof, De Houwer, De Schryver, and Verschuere (2015) provided evidence supporting the role of inhibition in lying. In the study of Debey et al., inhibitory skill was measured in terms of the size of the lie effect. However, to provide convincing evidence that delta plots highlight the role of response inhibition in lying, inhibitory ability must be evaluated independently from the size of the lie effect. After replicating original findings, this article shows that a delta plot analysis does not differentiate individuals with different inhibitory abilities, when inhibitory skill is measured by means of the Stop Signal Task, instead of the size of the lie effect. This suggests that researchers should be cautious when making conclusions about cognitive mechanisms based on the sole analysis of delta plots.

The detection of faked identity using unexpected questions and mouse dynamics

The detection of faked identities is a major problem in security. Current memory-detection techniques cannot be used as they require prior knowledge of the respondent’s true identity. Here, we report a novel technique for detecting faked identities based on the use of unexpected questions that may be used to check the respondent identity without any prior autobiographical information. While truth-tellers respond automatically to unexpected questions, liars have to “build” and verify their responses. This lack of automaticity is reflected in the mouse movements used to record the responses as well as in the number of errors. Responses to unexpected questions are compared to responses to expected and control questions (i.e., questions to which a liar also must respond truthfully). Parameters that encode mouse movement were analyzed using machine learning classifiers and the results indicate that the mouse trajectories and errors on unexpected questions efficiently distinguish liars from truth-tellers. Furthermore, we showed that liars may be identified also when they are responding truthfully. Unexpected questions combined with the analysis of mouse movement may efficiently spot participants with faked identities without the need for any prior information on the examinee.

The "good cop, bad cop" effect in the RT-based concealed information test: exploring the effect of emotional expressions displayed by a virtual investigator

Concealing the possession of relevant information represents a complex cognitive process, shaped by contextual demands and individual differences in cognitive and socio-emotional functioning. The Reaction Time-based Concealed Information Test (RT-CIT) is used to detect concealed knowledge based on the difference in RTs between denying recognition of critical (probes) and newly encountered (irrelevant) information. Several research questions were addressed in this scenario implemented after a mock crime. First, we were interested whether the introduction of a social stimulus (facial identity) simulating a virtual investigator would facilitate the process of deception detection. Next, we explored whether his emotional displays (friendly, hostile or neutral) would have a differential impact on speed of responses to probe versus irrelevant items. We also compared the impact of introducing similar stimuli in a working memory (WM) updating context without requirements to conceal information. Finally, we explored the association between deceptive behavior and individual differences in WM updating proficiency or in internalizing problems (state / trait anxiety and depression). Results indicated that the mere presence of a neutral virtual investigator slowed down participants' responses, but not the appended lie-specific time (difference between probes and irrelevants). Emotional expression was shown to differentially affect speed of responses to critical items, with positive displays from the virtual examiner enhancing lie-specific time, compared to negative facial expressions, which had an opposite impact. This valence-specific effect was not visible in the WM updating context. Higher levels of trait / state anxiety were related to faster responses to probes in the negative condition (hostile facial expression) of the RT-CIT. These preliminary findings further emphasize the need to take into account motivational and emotional factors when considering the transfer of deception detection techniques from the laboratory to real-life settings.