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The present study examined the effectiveness of a Modified-Comparison Questions Technique, used in conjunction with the polygraph, to differentiate between common travelers, drug traffickers, and terrorists at transportation hubs. Two experiments were conducted using a mock crime paradigm. In Experiment 1, we randomly assigned 78 participants to either a drug condition, where they packed and lied about illicit drugs in their luggage, or a control condition, where they did not pack or lie about any illegal items. In Experiment 2, we randomly assigned 164 participants to one of the two conditions in Experiment 1 or an additional bomb condition, where they packed and lied about a bomb in their luggage. For both experiments, we assessed participants’ RR interval, heart rate, peak-to-peak amplitude of Galvanic Skin Response (GSR) and all three combined, using Discriminant Analyses to determine the classification accuracy of participants in each condition. In both experiments, we found decelerated heart rates and increased peak-to-peak amplitude of GSR in guilty participants when lying in response to questions regarding their crime. We also found accurate classifications of participants, in both Experiment 1 (drug vs. control: 84.2% vs. 82.5%) and Experiment 2 (drug vs. control: 82:1% vs. 95.1%; bomb vs. control: 93.2% vs. 95.1%; drug vs. bomb: 92.3% vs. 90.9%), above chance level. These findings indicate that Modified-CQT, combined with a polygraph test, is a viable method for investigating suspects of drug trafficking and terrorism at transportation hubs such as train stations and airports.

An individual's ability to discriminate lies from truth is far from accurate, and is poorly related to an individual's confidence in his/her detection. Both law enforcement and non-professional interviewers base their evaluations of truthfulness on experiential criteria, including emotional and expressive features, cognitive complexity, and paraverbal aspects of interviewees' reports. The current experimental study adopted two perspectives of investigation: the first is aimed at assessing the ability of naïve judges to detect lies/truth by watching a videotaped interview; the second takes into account the interviewee's detectability as a liar or as telling the truth by a sample of judges. Additionally, this study is intended to evaluate the criteria adopted to support lie/truth detection and relate them with accuracy and confidence of detection. Results showed that judges' detection ability was moderately accurate and associated with a moderate individual sense of confidence, with a slightly better accuracy for truth detection than for lie detection. Detection accuracy appeared to be negatively associated with detection confidence when the interviewee was a liar, and positively associated when the interviewee was a truth-teller. Furthermore, judges were found to support lie detection through criteria concerning emotional features, and to sustain truth detection by taking into account the cognitive complexity and the paucity of expressive manifestations related with the interviewee's report. The present findings have implications for the judicial decision on witnesses' credibility.

Most of deception research has focused on past events that were either completely truthful or a complete fabrication. However, people often tell a mixture of truths and lies. This could enable investigators to make within-subjects comparisons between different themes discussed in one interview, which we examined in the current experiment. Seventy-three participants took part in the experiment and were asked to either tell the truth about two themes, or to tell the truth about one theme and lie about the second theme in a HUMINT setting. Results showed that examining the differences in the amount of detail provided by the interviewees for each theme- obtained through a Theme-Selection strategy (a within-subjects measure)- yielded stronger results than examining differences between truth tellers and liars based on the entire interview without accounting for themes (between-subjects measure). The present study therefore highlighted the effectiveness of within-subjects measurements to both discriminate truth tellers from liars and to discover which section of a statement is false.

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.

The use of faked identities is a current issue for both physical and online security. In this paper, we test the differences between subjects who report their true identity and the ones who give fake identity responding to control, simple, and complex questions. Asking complex questions is a new procedure for increasing liars' cognitive load, which is presented in this paper for the first time. The experiment consisted in an identity verification task, during which response time and errors were collected. Twenty participants were instructed to lie about their identity, whereas the other 20 were asked to respond truthfully. Different machine learning (ML) models were trained, reaching an accuracy level around 90–95% in distinguishing liars from truth tellers based on error rate and response time. Then, to evaluate the generalization and replicability of these models, a new sample of 10 participants were tested and classified, obtaining an accuracy between 80 and 90%. In short, results indicate that liars may be efficiently distinguished from truth tellers on the basis of their response times and errors to complex questions, with an adequate generalization accuracy of the classification models.

Keywords: lie detection; memory detection; forensic psychiatry; criminal cases; translational application EN lie detection memory detection forensic psychiatry criminal cases translational application 1 3 3 05/27/20 20200525 NES 200525 "Deceiving others. Two interesting papers cover the topic of verbal lie detection and underline the need of more strategy-based research in the field of verbal lie detection. Two papers cover the topic of detection of malingered amnesia for the crime. [Extracted from the article]

Since time immemorial, lying has been a part of everyday life. For this reason, it has become a subject of interest in several disciplines, including psychology. The purpose of this article is to provide a general overview of the literature and thinking to date about the evolution of lie detection techniques. The first part explores ancient methods recorded circa 1000 B.C. (e.g., God’s judgment in Europe). The second part describes technical methods based on sciences such as phrenology, polygraph and graphology. This is followed by an outline of more modern-day approaches such as FACS (Facial Action Coding System), functional MRI, and Brain Fingerprinting. Finally, after the familiarization with the historical development of techniques for lie detection, we discuss the scope for new initiatives not only in the area of designing new methods, but also for the research into lie detection itself, such as its motives and regulatory issues related to deception.

The present study examined the effectiveness of a Modified-Comparison Questions Technique, used in conjunction with the polygraph, to differentiate between common travelers, drug traffickers, and terrorists at transportation hubs. Two experiments were conducted using a mock crime paradigm. In Experiment 1, we randomly assigned 78 participants to either a drug condition, where they packed and lied about illicit drugs in their luggage, or a control condition, where they did not pack or lie about any illegal items. In Experiment 2, we randomly assigned 164 participants to one of the two conditions in Experiment 1 or an additional bomb condition, where they packed and lied about a bomb in their luggage. For both experiments, we assessed participants' RR interval, heart rate, peak-to-peak amplitude of Galvanic Skin Response (GSR) and all three combined, using Discriminant Analyses to determine the classification accuracy of participants in each condition. In both experiments, we found decelerated heart rates and increased peak-to-peak amplitude of GSR in guilty participants when lying in response to questions regarding their crime. We also found accurate classifications of participants, in both Experiment 1 (drug vs. control: 84.2% vs. 82.5%) and Experiment 2 (drug vs. control: 82:1% vs. 95.1%; bomb vs. control: 93.2% vs. 95.1%; drug vs. bomb: 92.3% vs. 90.9%), above chance level. These findings indicate that Modified-CQT, combined with a polygraph test, is a viable method for investigating suspects of drug trafficking and terrorism at transportation hubs such as train stations and airports. [ABSTRACT FROM AUTHOR]

In the present work, we introduce the Miami University Deception Detection Database (MU3D), a free resource containing 320 videos of target individuals telling truths and lies. Eighty (20 Black female, 20 Black male, 20 White female, and 20 White male) different targets were recorded speaking honestly and dishonestly about their social relationships. Each target generated four different videos (i.e., positive truth, negative truth, positive lie, negative lie), yielding 320 videos fully crossing target race, target gender, statement valence, and statement veracity. These videos were transcribed by trained research assistants and evaluated by naïve raters. Descriptive analyses of the video characteristics (e.g., length) and subjective ratings (e.g., target attractiveness) are provided. The stimuli and an information codebook can be accessed free of charge for academic research purposes from http://hdl.handle.net/2374.MIA/6067. The MU3D offers scholars the ability to conduct research using standardized stimuli that can aid in building more comprehensive theories of interpersonal sensitivity, enhance replication among labs, facilitate the use of signal detection analyses, and promote consideration of race, gender, and their interactive effects in deception detection research. [ABSTRACT FROM AUTHOR]

An individual's ability to discriminate lies from truth is far from accurate, and is poorly related to an individual's confidence in his/her detection. Both law enforcement and non-professional interviewers base their evaluations of truthfulness on experiential criteria, including emotional and expressive features, cognitive complexity, and paraverbal aspects of interviewees' reports. The current experimental study adopted two perspectives of investigation: the first is aimed at assessing the ability of naïve judges to detect lies/truth by watching a videotaped interview; the second takes into account the interviewee's detectability as a liar or as telling the truth by a sample of judges. Additionally, this study is intended to evaluate the criteria adopted to support lie/truth detection and relate them with accuracy and confidence of detection. Results showed that judges' detection ability was moderately accurate and associated with a moderate individual sense of confidence, with a slightly better accuracy for truth detection than for lie detection. Detection accuracy appeared to be negatively associated with detection confidence when the interviewee was a liar, and positively associated when the interviewee was a truth-teller. Furthermore, judges were found to support lie detection through criteria concerning emotional features, and to sustain truth detection by taking into account the cognitive complexity and the paucity of expressive manifestations related with the interviewee's report. The present findings have implications for the judicial decision on witnesses' credibility. [ABSTRACT FROM AUTHOR]

The relationship between nonverbal communication and deception continues to attract much interest, but there are many misconceptions about it. In this review, we present a scientific view on this relationship. We describe theories explaining why liars would behave differently from truth tellers, followed by research on how liars actually behave and individuals' ability to detect lies. We show that the nonverbal cues to deceit discovered to date are faint and unreliable and that people are mediocre lie catchers when they pay attention to behavior. We also discuss why individuals hold misbeliefs about the relationship between nonverbal behavior and deception—beliefs that appear very hard to debunk. We further discuss the ways in which researchers could improve the state of affairs by examining nonverbal behaviors in different ways and in different settings than they currently do. [ABSTRACT FROM AUTHOR]

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The accuracy of lie detection is a highly debated topic in the science community, and it has been determined that there are many conditions in which the “truth” simply cannot be determined (Saxe 1991). The purpose of this experiment was to decide whether the truthfulness or falsehood of the responses of a set of randomly selected test subjects could be determined by observation of their behavior. Based on prior knowledge, it was hypothesized that the truthfulness of the test subjects could not be determined based off analysis of their behavior. The experiment consisted of interviewing a group of test subjects in a series of two trials of the same questions, one that they would answer truthfully and one that they would answer untruthfully. The subjects chose which trial they told the truth and which they did not. Their behavior was observed for both trials, and the observations were recorded. The presence of certain common behavioral traits was graphed, and revealed that there were in fact patterns in the overall behavior that distinguished between true and false responses. It was concluded that for this group of subjects, certain behavioral characteristics, such as lack of eye contact or lack of emotions present, indicated that the subject was lying when answering questions. [ABSTRACT FROM AUTHOR]

Existing research is inconclusive regarding the influence of perceiver gender and target gender on lie detection. Researchers have offered a number of conclusions regarding gender effects in deception detection (e.g., women are better at lie detection than men, participant and target gender interact in predicting deception detection accuracy, there are no gender effects in deception detection). In the current work, we revisit the question of whether and how gender influences lie detection, employing a large database of controlled stimuli, a large sample size, and the analytical advantages provided by signal detection theory. Participants viewed videos of male and female targets telling truths and lies about interpersonal relationships, and after each video, they rendered a truth or lie judgment. Female targets were easier to "read" (i.e., greater sensitivity) and were called liars more frequently than male targets. No effects of participant gender were observed. This work sheds light on an important issue in the lie detection literature (i.e., does gender matter?), and it identifies important considerations for understanding gender biases and cross-gender social interactions. [ABSTRACT FROM AUTHOR]

Inconsistency is often considered an indication of deceit. The conceptualization of consistency used in deception research, however, has not made a clear distinction between two concepts long differentiated by philosophers: coherence and correspondence. The existing literature suggests that coherence is not generally useful for deception detection. Correspondence, however, appears to be quite useful. The present research developed a model of how correspondence is utilized to make judgments, and this article reports on four studies designed to elaborate on the model. The results suggest that judges attend strongly to correspondence and that they do so in an additive fashion. As noncorrespondent information accumulates, an increasingly smaller proportion of judges make truthful assessments of guilty suspects. This work provides a basic framework for examining how information is utilized to make deception judgments and forms the correspondence and coherence module of truth-default theory. [ABSTRACT FROM AUTHOR]

Summary The verifiability approach (VA) is a lie‐detection tool that examines reported checkable details. Across two studies, we attempt to exploit liar's preferred strategy of repeating information by examining the effect of questioning adult interviewees before the VA. In Study 1, truth tellers (n = 34) and liars (n = 33) were randomly assigned to either an initial open or closed questioning condition. After initial questioning, participants were interviewed using the VA. In Study 2, truth tellers (n = 48) and liars (n = 48) were interviewed twice, with half of each veracity group randomly assigned to either the Information Protocol (an instruction describing the importance of reporting verifiable details) or control condition. Only truth tellers revised their initial statement to include verifiable detail. This pattern was most pronounced when initial questioning was open (Study 1) and when the information protocol was employed (Study 2). Thus, liar's preferred strategy of maintaining consistency between statements appears exploitable using the VA. [ABSTRACT FROM AUTHOR]

Muscle Response Testing (MRT) is an assessment tool estimated to be used by over one million people worldwide, mainly in the field of alternative health care. During a test, a practitioner applies a force on a patient's isometrically contracted muscle for the purpose of gaining information about the patient in order to guide care. The practitioner notes the patient's ability or inability to resist the force and interprets the outcome according to predetermined criteria. Though recent research supports the validity of MRT, little is known about its mechanism of action. Nevertheless, its causation is often attributed to an ideomotor effect, which can be defined as muscular activity, potentially nonconscious, and seemingly brought about by a third-party operator. Accordingly, the aim of this study is to investigate whether the ideomotor effect is a plausible explanation of action for MRT. Methods: This is a retrospective, observational study of data extraction from a previously reported study of the diagnostic accuracy of MRT used to distinguish true from false statements. Additional analysis was carried out on the dataset of assessing for potential sources of bias- both practitioner bias and patient bias. Results: When practitioners were blind, they achieved a mean MRT accuracy of 65.9% (95% CI 62.3-69.5), and when they were not blind, 63.2% (95% CI 58.3-68.1). No significant difference was found between these scores (p = 0.37). When practitioners were intermittently misled, the mean MRT accuracy decreased to 56.6% (95% CI 49.4-63.8), which proved to be significantly different from when the practitioners were blind (p = 0.02), yet not significantly different from then the practitioners were not blind (p = 0.11). In addition, no evidence of patient bias was uncovered. Summary: The results of this study demonstrate that when comparing blind and not blind conditions, the practitioner evokes no influence, so it is unlikely that the practitioner is responsible for an ideomotor effect. Likewise, the patient has been shown to produce no significant influence either, so it is also unlikely that the patient is responsible for an ideomotor effect. The limitations of this study are those of any retrospective, observational study in that data were not collected to answer the specific research question of this study. Future research should include a study specifically designed to answer this question, for example, intentionally attempting to induce bias in the practitioner. In summary, the ideomotor explanation of MRT should be regarded as obsolete until such a time as a more plausible explanation of its mechanism of action is established. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: The current experiment examined the use of a model statement for aiding lie detection and gathering additional information during interviews in which pairs of suspects were interviewed together (i.e., collective interviewing). A model statement is an example of an answer, unrelated to the topic under investigation, which is played to suspects to demonstrate how much information the interviewer wants them to provide in response to the question asked. Method: Pairs of truth‐tellers visited a restaurant together, whereas pairs of liars completed a mock crime. The task for all pairs was to convince an interviewer that they were visiting a restaurant together at the time the crime was committed. Half the truth‐telling pairs and half the lying pairs were exposed to a model statement, whilst the other halves were not. Results: Truth‐telling pairs were more detailed and showed more interactions than lying pairs, particularly in the model statement present condition. Conclusions: Being exposed to a model statement in a collective interview magnified the differences between pairs of truth‐tellers and pairs of liars in reporting detail and interacting with one another. A model statement is simple to implement and can be applied to many real‐world investigative interviewing settings whereby the focus is on lie detection and gathering as much information as possible. [ABSTRACT FROM AUTHOR]

Lying typically requires greater mental effort than telling the truth. Imposing cognitive load may improve lie detection by limiting the cognitive resources needed to lie effectively, thereby increasing the difference in speed between truths and lies. We test this hypothesis meta-analytically. Across 21 studies using response-time (RT) paradigms (11 unpublished; total N = 792), we consistently found that truth-telling was faster than lying, but found no evidence that imposing cognitive load increased that difference (Control, d = 1.45; Load, d = 1.28). Instead, load significantly decreased the lie–truth RT difference by increasing the RT of truths, g = −.18, p =.027. Our findings therefore suggest that imposing cognitive load does not necessarily improve RT-based lie detection, and may actually worsen it by taxing the mental system and thus impeding people's ability to easily—and thus quickly—tell the truth. [ABSTRACT FROM AUTHOR]

Detection of deception is of fundamental importance for everyday social life and might require "mindreading" (the ability to represent others' mental states). People with diminished mindreading, such as those with autism spectrum disorder (ASD), might be at risk of manipulation because of lie detection difficulties. In Experiment 1, performance among 216 neurotypical adults on a realistic lie detection paradigm was significantly negatively associated with number of ASD traits, but not with mindreading ability. Bayesian analyses complemented null hypothesis significance testing and suggested the data supported the alternative hypothesis in this key respect. Cross validation of results was achieved by randomly splitting the full sample into two subsamples of 108 and rerunning analyses. The association between lie detection and ASD traits held in both subsamples, showing the reliability of findings. In Experiment 2, lie detection was significantly impaired in 27 adults with a diagnosis of ASD relative to 27 matched comparison participants. Results suggest that people with ASD (or ASD traits) may be particularly vulnerable to manipulation and may benefit from lie detection training. Autism Res2018, 11: 1129–1137. © 2018 The Authors Autism Research published by International Society for Autism Research and Wiley Periodicals, Inc. Lay Summary: Detection of deception is of fundamental importance for everyday social life. People with diminished understanding of other minds, such as those with autism spectrum disorder (ASD), might be at risk of manipulation because of lie detection difficulties. We found that lie detection ability was related to how many ASD traits neurotypical people manifested and also was significantly diminished among adults with a full diagnosis of ASD. [ABSTRACT FROM AUTHOR]

Computer technology has advanced to a greater extent which leads to increase in cyber crime committed in recent years. The detection of cyber crime is not an easy task. From the literature, many researchers used various technologies to detect the cyber crime. In this paper, performance evaluation of various techniques are analysed to determine the cyber criminal. Firstly the detection of synthetic identity theft is checked. Secondly, the intrusion detection is checked using the honey pot security mechanism. Thirdly, the detection is further strengthened using the lie detection technique where the false speech of a person is determined. Finally by analysing the user profile, the detection of cyber crime is done using the clustering techniques. Synthetic Identity Theft method performs better than the remaining methods when considered for evaluation. Experimental results show that comparison of the final list of criminal users and the list of criminals determined, the number of genuine users eliminated are 41 out of 100 users, where as the number of genuine users eliminated from other methods are 16, 36 and 38 only. The number of attributes used is only 4, where as the number of attributes used for other methods are 5, 10 and 25. The percentage of performance metrics is also 37.1 and gradient is 31.1 which are better compared to other methods considered for performance analysis. [ABSTRACT FROM AUTHOR]

Filing a false police report is a crime that has dire consequences on both the individual and the system. In fact, it may be charged as a misdemeanor or a felony. For the society, a false report results in the loss of police resources and contamination of police databases used to carry out investigations and assessing the risk of crime in a territory. In this research, we present VeriPol , a model for the detection of false robbery reports based solely on their text. This tool, developed in collaboration with the Spanish National Police, combines Natural Language Processing and Machine Learning methods in a decision support system that provides police officers the probability that a given report is false. VeriPol has been tested on more than 1000 reports from 2015 provided by the Spanish National Police. Empirical results show that it is extremely effective in discriminating between false and true reports with a success rate of more than 91%, improving by more than 15% the accuracy of expert police officers on the same dataset. The underlying classification model can be analysed to extract patterns and insights showing how people lie to the police (as well as how to get away with false reporting). In general, the more details provided in the report, the more likely it is to be honest. Finally, a pilot study carried out in June 2017 has demonstrated the usefulness of VeriPol on the field. [ABSTRACT FROM AUTHOR]

The use of faked identities is a current issue for both physical and online security. In this paper, we test the differences between subjects who report their true identity and the ones who give fake identity responding to control, simple, and complex questions. Asking complex questions is a new procedure for increasing liars' cognitive load, which is presented in this paper for the first time. The experiment consisted in an identity verification task, during which response time and errors were collected. Twenty participants were instructed to lie about their identity, whereas the other 20 were asked to respond truthfully. Different machine learning (ML) models were trained, reaching an accuracy level around 90-95% in distinguishing liars from truth tellers based on error rate and response time. Then, to evaluate the generalization and replicability of these models, a new sample of 10 participants were tested and classified, obtaining an accuracy between 80 and 90%. In short, results indicate that liars may be efficiently distinguished from truth tellers on the basis of their response times and errors to complex questions, with an adequate generalization accuracy of the classification models. [ABSTRACT FROM AUTHOR]

Previous research has shown that inconsistencies across repeated interviews do not indicate deception because liars deliberately tend to repeat the same story. However, when a strategic interview approach that makes it difficult for liars to use the repeat strategy is used, both consistency and evasive answers differ significantly between truth tellers and liars, and statistical software (binary logistic regression analyses) can reach high classification rates (Masip et al., 2016b). Yet, if the interview procedure is to be used in applied settings the decision process will be made by humans, not statistical software. To address this issue, in the current study, 475 college students (Experiment 1) and 142 police officers (Experiment 2) were instructed to code and use consistency, evasive answers, or a combination or both before judging the veracity of Masip et al.'s (2016b) interview transcripts. Accuracy rates were high (60% to over 90%). Evasive answers yielded higher rates than consistency, and the combination of both these cues produced the highest accuracy rates in identifying both truthful and deceptive statements. Uninstructed participants performed fairly well (around 75% accuracy), apparently because they spontaneously used consistency and evasive answers. The pattern of results was the same among students, all officers, and veteran officers only, and shows that inconsistencies between interviews and evasive answers reveal deception when a strategic interview approach that hinders the repeat strategy is used.

The use of modern technology has led to a scientific revolution in the field of establishing guilt. Consequently, this has given rise to a great debate about its legitimacy among criminal law scholars, especially as its use may result in the violation of individual rights and human dignity. This raises the question about the impact of using modern technology in the process of establishing guilt on human rights. Therefore, this study aims to evaluate the procedures of establishing guilt using modern technology methods adopted by the Algerian legislator, and to what extent individual’s rights and liberties are respected during those procedures. This study compares between rules of establishing guilt using modern technology in Algerian legislation and other legislation. This aims to offer some recommendations that help legislators keep pace with scientific and technical advancements. It also suggests ways to achieve a balance between using modern technology and respecting legal guarantees that prevent the infringement of individual rights and liberties. Results of the study show the significant negative impact of some modern evidences used to establish guilt. This is shown in the violation of the rights and liberties of individuals, in addition to inaccurate results obtained by using such evidences. This study recommends that the Algerian legislator clarify their position regarding modern means of establishing guilt, which must be unambiguously regulated and surrounded by adequate guarantees that protect the rights and liberties of individuals. Keywords: Establishing guilt, DNA, hypnosis, lie detection, electronic surveillance, human rights.

Lie detection based on nonverbal behavior is not a standard method, it is an intuitive process, applied by lay persons, but also professionals. Some of the major sources (e.g. widespread Interrogation Manual by F. Inbau et al., 2004) offer clear recommendations about the nonverbal behavior of liars to investigators of serious crime. These findings are not supported by the research, moreover they can lead to lowering the ability to detect lie (Blair, Kooi 2004). Another topic is mapping the skills of professionals (police officers, members of the secret services) and non-specialists to detect lies by nonverbal signs. Across the studies (with few exceptions) a low performance in the task of detecting lies by nonverbal expressions (Ekman P., 1996; Vrij, 2004 and others) is found. The levels of success are usually around the level of chance. The potential reasons for such results are analyzed (e.g. Blair, Kooi, 2004). However a group of psychologists led by P. Ekman and M. O'Sullivan (O'Sullivan, 2007) managed to find in their years lasting research a group of people whose ability to detect lies is well above the population average. This group is diverse in terms of age, interests and professions, all of them come from the USA. There were certain common features found in this group and also a focus on similar phenomena in the detection of lying. The main goal and research question is to find out: what is the success rate of differentiation between lies and truths in this specific professional group of Czech population, is it the same or different from the results reported in the context of available resources. The research will focus on the ability of respondents to determine the truth or deceit on the basis of non-verbal and paraverbal expressions of observed subjects, with focus on specific professional groups - mainly police workers. We assume, that the police officers are frequently in the contact with people, who are not willing to reveal critical information or who are motivated to lie. The procedure: The material consisted of short video sections originating from real investigation of serious crime. After the pilot study the stimuli material has been created consisting of 21 video-sections lasting 30 seconds, the sound of the videos was filtered, so the paraverbal characteristics were maintained, but the content of the speech was unclear. The research sample consisted of 197 police officers from 5 departments. Selected results: The TRUTH detection accuracy - (the accuracy of correct evaluation of the truth-telling people on the video) was situated between 0,25 (25%) to 0,75 (75%). The LIE detection accuracy - was situated between 0,44 (44%) to 1 (100%). The overall accuracy (means combined accuracy of lie and truth detection) was situated between 0,33 (33%) and 0.86 (86%). 5 respondents obtained results, that were above the average of the group in all the three categories (truth, lie, overall). The discussion: The results indicate that (among others) we can find so called lie bias among the police workers, which is common in the similar professional settings and it involves higher expectations of lie and deceit on the side of the communication partner. In the common population the opposite tendency - so called truth bias - tendency to evaluate others (situations, behavior, statements) as truthful is found. The study managed to find police workers, who obtained better results than guessing and also better than the average of the tested group. The main limit of the study is probably the lack of repeated retest of the sample. This and other findings were involved into the police training focused on communication and lie during criminal investigation, which is not systematic in Czech Republic. The plan is to test also other professional groups in the future.