Which Lie Detection Tools are Ready for Use in the Criminal Justice System?

The trajectory of crime: Integrating mouse-tracking into concealed memory detection

The autobiographical implicit association test (aIAT) is an approach of memory detection that can be used to identify true autobiographical memories. This study incorporates mouse-tracking (MT) into aIAT, which offers a more robust technique of memory detection. Participants were assigned to mock crime and then performed the aIAT with MT. Results showed that mouse metrics exhibited IAT effects that correlated with the IAT effect of RT and showed differences in autobiographical and irrelevant events while RT did not. Our findings suggest the validity of MT in offering measurement of the IAT effect. We also observed different patterns in mouse trajectories and velocity for autobiographical and irrelevant events. Lastly, utilizing MT metric, we identified that the Past Negative Score was positively correlated with IAT effect. Integrating the Past Negative Score and AUC into computational models improved the simulation results. Our model captured the ubiquitous implicit association between autobiographical events and the attribute True, and offered a mechanistic account for implicit bias. Across the traditional IAT and the MT results, we provide evidence that MT-aIAT can better capture the memory identification and with implications in crime detection.

Fast & furious: Rejecting the hypothesis that secondary psychopathy improves reaction time-based concealed information detection

Deception, a complex aspect of human behavior, is inherently difficult to detect directly. A valid alternative involves memory detection, particularly through methods such as the Reaction-Time based Concealed Information Test (RT-CIT). The RT-CIT assesses whether an individual possesses specific knowledge by presenting various probe (familiar) items amidst irrelevant (unfamiliar) items. The task-required "unfamiliar" response to probes may induce a response conflict. Resolving this conflict, by inhibiting the automatic "familiar" response, takes time and slows probe RTs-a phenomenon known as the RT-CIT effect. Notably, secondary psychopathy is characterized by disinhibition and impulsivity, traits which may hinder the ability to effectively manage experienced conflict. Therefore, we hypothesized that secondary psychopathy would be associated with an elevated RT-CIT effect. To investigate this hypothesized relation, we conducted a pre-registered study (n = 86, student sample), employing a novel CIT paradigm that incorporates no-go trials to assess response inhibition capacity. Psychopathic traits were measured using the Levenson Self-Report Psychopathy (LSRP) scale, while the Barratt Impulsiveness Scale (BIS-11) assessed impulsivity. The novel CIT paradigm revealed impressive detection efficiency. However, contrary to our expectations, we observed no significant correlation between the RT-CIT effect and secondary psychopathic traits (BF01 = 6.98). This cautiously suggests that while secondary psychopathic tendencies do not improve RT-CIT validity, they also do not compromise it. Although future investigations should explore more diverse contexts and populations, this tentative finding is reassuring and underscores the robustness of the CIT paradigm.

Verbal lie detection using Large Language Models

Human accuracy in detecting deception with intuitive judgments has been proven to not go above the chance level. Therefore, several automatized verbal lie detection techniques employing Machine Learning and Transformer models have been developed to reach higher levels of accuracy. This study is the first to explore the performance of a Large Language Model, FLAN-T5 (small and base sizes), in a lie-detection classification task in three English-language datasets encompassing personal opinions, autobiographical memories, and future intentions. After performing stylometric analysis to describe linguistic differences in the three datasets, we tested the small- and base-sized FLAN-T5 in three Scenarios using 10-fold cross-validation: one with train and test set coming from the same single dataset, one with train set coming from two datasets and the test set coming from the third remaining dataset, one with train and test set coming from all the three datasets. We reached state-of-the-art results in Scenarios 1 and 3, outperforming previous benchmarks. The results revealed also that model performance depended on model size, with larger models exhibiting higher performance. Furthermore, stylometric analysis was performed to carry out explainability analysis, finding that linguistic features associated with the Cognitive Load framework may influence the model's predictions.

From criminal interrogations to investigative interviews: a bibliometric study

This paper presents the results of a bibliometric study providing a comprehensive overview of the social science research conducted on criminal interrogations and investigative interviews since the 1900s. The objectives are to help researchers to further understand the research field, to better communicate research findings to practitioners, to help practitioners understand the breadth of scientific knowledge on criminal interrogations and investigative interviews, and to foster dialog between researchers and practitioners. To begin, after a brief description of Web of Science, we describe how we developed our database on criminal interrogations and investigative interviews. Then, we report the yearly evolution of articles, the journals where they were published, the research areas covered by this research field, as well as the authors, the institutions and the countries that published the most on a variety of topics related to criminal interrogations and investigative interviews. Finally, we present the most used keywords and the most cited articles, and examine the research on questionable tactics and techniques in the research field of criminal interrogations and investigative interviews. This paper ends with a critical look at the results, for the benefit of researchers and practitioners interested in criminal interrogations and investigative interviews.

A Semi-Supervised Speech Deception Detection Algorithm Combining Acoustic Statistical Features and Time-Frequency Two-Dimensional Features

Human lying is influenced by cognitive neural mechanisms in the brain, and conducting research on lie detection in speech can help to reveal the cognitive mechanisms of the human brain. Inappropriate deception detection features can easily lead to dimension disaster and make the generalization ability of the widely used semi-supervised speech deception detection model worse. Because of this, this paper proposes a semi-supervised speech deception detection algorithm combining acoustic statistical features and time-frequency two-dimensional features. Firstly, a hybrid semi-supervised neural network based on a semi-supervised autoencoder network (AE) and a mean-teacher network is established. Secondly, the static artificial statistical features are input into the semi-supervised AE to extract more robust advanced features, and the three-dimensional (3D) mel-spectrum features are input into the mean-teacher network to obtain features rich in time-frequency two-dimensional information. Finally, a consistency regularization method is introduced after feature fusion, effectively reducing the occurrence of over-fitting and improving the generalization ability of the model. This paper carries out experiments on the self-built corpus for deception detection. The experimental results show that the highest recognition accuracy of the algorithm proposed in this paper is 68.62% which is 1.2% higher than the baseline system and effectively improves the detection accuracy.

The Science of Lie Detection by Verbal Cues: What Are the Prospects for Its Practical Applicability?

There is agreement among researchers that no simple verbal cues to deception detectable by humans have been demonstrated. This paper examines the evidence for the most prominent current methods, critically considers the prevailing research strategy, proposes a taxonomy of lie detection methods and concludes that two common types of approach are unlikely to succeed. An approach to lie detection is advocated that derives both from psychological science and common sense: When an interviewee produces a statement that contradicts either a previous statement by the same person or other information the authorities have, it will in many cases be obvious to interviewer and interviewee that at least one of the statements is a lie and at the very least the credibility of the witness is reduced. The literature on Strategic Use of Evidence shows that features of interviews that foster such revelatory and self-trapping situations have been established to be a free account and the introduction of independent information late and gradually into the proceedings, and tactics based on these characteristics constitute the best current general advice for practitioners. If any other approach 1 day challenges this status quo, it is likely to be highly efficient automated systems.

Assessing Deception in Questionnaire Surveys With Eye-Tracking

Deceit often occurs in questionnaire surveys, which leads to the misreporting of data and poor reliability. The purpose of this study is to explore whether eye-tracking could contribute to the detection of deception in questionnaire surveys, and whether the eye behaviors that appeared in instructed lying still exist in spontaneous lying. Two studies were conducted to explore eye movement behaviors in instructed and spontaneous lying conditions. The results showed that pupil size and fixation behaviors are both reliable indicators to detect lies in questionnaire surveys. Blink and saccade behaviors do not seem to predict deception. Deception resulted in increased pupil size, fixation count and duration. Meanwhile, respondents focused on different areas of the questionnaire when lying versus telling the truth. Furthermore, in the actual deception situation, the linear support vector machine (SVM) deception classifier achieved an accuracy of 74.09%. In sum, this study indicates the eye-tracking signatures of lying are not restricted to instructed deception, demonstrates the potential of using eye-tracking to detect deception in questionnaire surveys, and contributes to the questionnaire surveys of sensitive issues.

Revenge is not blind: Testing the ability of retribution to justify dishonesty

In two studies, we tested the power of revenge as a justification mechanism that enables people to cheat with a clear conscience. Specifically, we explored the effects of prior dishonesty and unfairness towards participants on their subsequent moral behavior, as well as the physiological arousal associated with it. To this end, we employed a two-phase procedure. In the first phase, participants played one round of a bargaining game (the Ultimatum game in Study 1 and the Dictator game in Study 2) in which we manipulated whether the players had been treated (un)fairly and (dis)honestly by their opponent. In the second phase, they did a perceptual task that allowed them to cheat for monetary gain at the expense of their opponent from the first phase. In Study 1, participants also took a lie detector test to assess whether their dishonesty in the second phase could be detected. The behavioral results in both studies indicated that the opponent’s dishonesty was a stronger driver than the opponent’s unfairness for cheating as a form of retaliation. However, the physiological arousal results suggest that feeling mistreated in general (and not just cheated) allowed the participants to get revenge by cheating the offender while dismissing their associated guilt feelings.

Justice and Nonverbal Communication in a Post-pandemic World: An Evidence-Based Commentary and Cautionary Statement for Lawyers and Judges

On 11 March 2020, the World Health Organization officially declared COVID-19 a pandemic. The new physical distancing rules have had many consequences, some of which are felt throughout the justice system. Courts across the world limited their operations. Nonetheless, given that justice delayed is justice denied, many jurisdictions have turned to technologies for urgent matters. This paper offers an evidence-based comment and caution for lawyers and judges who could be inclined, for concerns such as cost and time saving, to permanently step aside from in-person trials. Using nonverbal communication research, in conjunction with American and Canadian legal principles, we argue that such a decision could harm the integrity of the justice system.

The Lie Deflator – The effect of polygraph test feedback on subsequent (dis)honesty

Despite its controversial status, the lie detection test is still a popular organizational instrument for credibility assessment. Due to its popularity, we examined the effect of the lie-detection test feedback on subsequent moral behavior. In three studies, participants could cheat to increase their monetary payoff in two consecutive phases. Between these two phases the participants underwent a mock polygraph test and were randomly given Deception Indicated (DI) or No Deception Indicated (NDI) assigned feedback. Then, participants engaged in the second phase of the task and their level of dishonesty was measured. Study 1 showed that both NDI and DI feedback (but not the control) reduced cheating behavior on the subsequent task. However, Study 2 showed that the mere presence of the lie-detection test (without feedback) did not produce the same effect. When the role of the lie detector as a moral reminder was cancelled out in Study 3, feedback had no effect on the magnitude of cheating behavior. However, cheaters who were given NDI feedback exhibited a lower level of physiological arousal than cheaters who were given DI feedback. These results suggest that lie detection tests can be used to promote honesty in the field, and that, while feedback type does not affect the magnitude of cheating, NDI may allow people to feel better about cheating.

The impact of lying about a traumatic virtual reality experience on memory

The goal of the present experiment was to examine the effect of certain (deceptive) strategies (e.g., false denial) on memory. Specifically, participants were shown a traumatic virtual reality (VR) video of an airplane crash. Following this, participants (N= 94) received questions concerning details from the VR scene in a baseline memory task. Then, participants could choose from 3 options how to cope in response to having experienced the VR scene: tell the truth, falsely deny, or fabricate. The majority opted to tell the truth (n = 81). A subsample of truth tellers were instructed to falsely deny having seen certain details. One week later, all participants received a source monitoring task in which they were asked (1) whether they remembered talking about these details during an interview, and (2) whether they remembered seeing certain details during the VR experience the week before. Participants had to tell the truth during this task. Participants who were instructed to falsely deny showed impaired memory for presented details that had previously been discussed (i.e., denial-induced forgetting) and seen in the VR scene. Also, the presentation of certain details in the baseline memory task seemed to inoculate participants who were instructed to falsely deny from experiencing memory impairment. The current experiment suggests that false denials can have adverse ramifications for memory for what is discussed and seen.

Police accuracy in truth/lie detection when judging baseline interviews

Research has shown that a comparable truth baseline (CTB) approach elicits more cues to deception and results in higher accuracy rates than a small talk baseline. Past research focused on laypeople's accuracy rates. We examined whether the CTB also has a positive effect on law enforcement personnel accuracy. In this study, 95 police officers judged 10 interviews, whereby half of the senders told the truth, and the other half lied about a mock undercover mission. Half of the interviews included only questioning about the event under investigation, whereas the other half also included questioning aimed at creating a CTB. Total and truth accuracy did not differ, but observers who watched interviews with a CTB obtained higher lie detection accuracy rates than those who watched interviews without the baseline questioning. Signal detection analyses showed that this effect could be attributed to a decreased response bias in the CTB condition.

Differentiating factitious psychological presentations from malingering: Implications for forensic practice

Practitioners and researchers have long been challenged with identifying deceptive response styles in forensic contexts, particularly when differentiating malingering from factitious presentations. The origins and the development of factitious disorders as a diagnostic classification are discussed, as well as the many challenges and limitations present with the current diagnostic conceptualization. As an alternative to a formal diagnosis, forensic practitioners may choose to consider most factitious psychological presentations (FPPs) as a dimensional construct that are classified like malingering as a V code. Building on Rogers' central motivations for malingering, the current article provides four explanatory models for FPPs; three of these parallel malingering (pathogenic, criminological, and adaptational) but differ in their central features. In addition, the nurturance model stresses how patients with FPPs attempt to use their relationship with treating professionals to fulfill their unmet psychological needs. Relying on these models, practical guidelines are recommended for evaluating FPPs in a forensic context.

Verbal Deception and the Model Statement as a Lie Detection Tool

We have been reliably informed by practitioners that police officers and intelligence officers across the world have started to use the Model Statement lie detection technique. In this article we introduce this technique. We describe why it works, report the empirical evidence that it works, and outline how to use it. Research examining the Model Statement only started recently and more research is required. We give suggestions for future research with the technique. The Model Statement technique is one of many recently developed verbal lie detection methods. We start this article with a short overview of the-in our view- most promising recent developments in verbal lie detection before turning our attention to the Model Statement technique.