Generating nonverbal indicators of deception in virtual reality training

Old Dominion University (ODU) has been performing research in the area of training using virtual environments. The research involves both computer controlled agents and human participants taking part in a peacekeeping scenario whereby various skills-based tasks are trained and evaluated in a virtual environment. The scenario used is a checkpoint operation in a typical third world urban area. The trainee is presented with innocuous encounters until a slightly noticeable but highly important change surfaces and the trainee must react in an appropriate fashion or risk injury to himself or his teammate. Although the tasks are mainly skill-based, many are closely related to a judgment that the trainee must make. In fact, judgment-based tasks are becoming prevalent and are also far more difficult to train and not well understood. Of interest is an understanding of these additional constraints encountered that illicit emotional response in judgment-based military scenarios. This paper describes ongoing research in creating affective component behaviors used to convey cues for anger, nervousness, and deception in Operations Other than War (OOTW) training

Detección de mentiras: estado de la cuestión y perspectivas de futuro

[EN]Background: Deception detection has been a longstanding concern throughout human history. It has also interested scientists, who have explored psychological and behavioral differences between liars and truth tellers, as well as ways to improve detection accuracy. Method: In recent years, substantial advances have been made in the fi eld. Some of these advances are briefly reviewed in the current article. Results: A description is provided of (a) research and contemporary theories on how people (try to) detect deception; (b) recent advances on strategic interviewing to detect deception; (c) the integrative findings of recent meta-analyses on systematic verbal lie detection approaches; and (d) several important aspects concerning psychophysiological detection of deception. Also, some emerging trends and research needs for the future are outlined at the end of the article. Conclusions: Deception detection research is a lively and dynamic area of applied psychology that has experienced substantial developments in recent times. Much (though not all) of these research efforts have focused on developing empirically-based lie-detection procedures to be used by practitioners (e.g., the police) in applied settings. A number of new topics are just starting to be examined. These novel research avenues will surely yield interesting new findings in the future.[ES]Antecedentes: la detección de mentiras ha interesado a la humanidad a lo largo de la historia. También a los científicos, quienes han explorado diferencias psicológicas y conductuales al mentir vs. decir la verdad, así como modos de aumentar la precisión de la detección. Método: recientemente se han hecho avances sustanciales en esta área. En el presente artículo se revisan algunos de ellos. Resultados: se describen (a) las investigaciones y teorías contemporáneas sobre cómo la gente (intenta) detecta(r) mentiras; (b) los avances en procedimientos estratégicos de entrevista para detectar mentiras; (c) los hallazgos de meta-análisis recientes sobre aproximaciones sistemáticas para la detección verbal del engaño; y (d) algunos aspectos importantes de la detección psicofisiológica de la mentira. Al final del artículo se esbozan algunas tendencias emergentes y necesidades de investigación de cara al futuro. Conclusiones: el área de investigación de la detección de mentiras ha experimentado grandes desarrollos en tiempos recientes. A menudo (aunque no siempre) se ha centrado en desarrollar procedimientos de detección de mentiras de base empírica para su utilización en contextos aplicados (p. ej., por la policía). Algunas vías de indagación novedosas están empezando a explorar temas nuevos y, seguramente, darán lugar a futuros hallazgos nuevos e interesantes

Deception Detection: An Exploration of Annotated Text-Based Cues

Do embedded textual cues in asynchronous communication affect deceptive message detection? The expanded use of social media and rich media applications in business make this an important issue. Prior research indicates deception commonly occurs in all forms of communication and people have difficulty detecting its use. Asynchronous online communications are no exception and offer users a variety of media choices which may complicate deception detection, particularly if the sender has strategically selected a channel intended to disguise their intentions. The current study investigated whether embedded, non-verbal cues in common media forms found in asynchronous online venues influenced deception detection. Drawing on media synchronicity theory, results suggest embedding non-verbal cues in the form of annotated text can enhance deception detection. Overall, the findings suggest managers must be wary of sender motivations, which can influence message veracity, particularly in low synchronicity environments where media is subject to edits and manipulations

Social Perception of Pedestrians and Virtual Agents Using Movement Features

In many tasks such as navigation in a shared space, humans explicitly or implicitly estimate social information related to the emotions, dominance, and friendliness of other humans around them. This social perception is critical in predicting others’ motions or actions and deciding how to interact with them. Therefore, modeling social perception is an important problem for robotics, autonomous vehicle navigation, and VR and AR applications. In this thesis, we present novel, data-driven models for the social perception of pedestrians and virtual agents based on their movement cues, including gaits, gestures, gazing, and trajectories. We use deep learning techniques (e.g., LSTMs) along with biomechanics to compute the gait features and combine them with local motion models to compute the trajectory features. Furthermore, we compute the gesture and gaze representations using psychological characteristics. We describe novel mappings between these computed gaits, gestures, gazing, and trajectory features and the various components (emotions, dominance, friendliness, approachability, and deception) of social perception. Our resulting data-driven models can identify the dominance, deception, and emotion of pedestrians from videos with an accuracy of more than 80%. We also release new datasets to evaluate these methods. We apply our data-driven models to socially-aware robot navigation and the navigation of autonomous vehicles among pedestrians. Our method generates robot movement based on pedestrians’ dominance levels, resulting in higher rapport and comfort. We also apply our data-driven models to simulate virtual agents with desired emotions, dominance, and friendliness. We perform user studies and show that our data-driven models significantly increase the user’s sense of social presence in VR and AR environments compared to the baseline methods.Doctor of Philosoph

Interpersonal deceit and lie-detection using computer-mediated communication

This thesis examines the use of computer-mediated communication for lie-detection and interpersonal deceit. The literature within the fields of lie-detection and mediated communication are reviewed and it is proposed that there is a lack of knowledge surrounding how people use CMC to deceive one another. Qualitative research was carried out in order to address this shortcoming, exploring the self-reported experiences of chat room users who have been exposed to online deceit. Reports were provided that describe the misrepresentation of age, gender, vocation, affection, and appearance. The importance of stereotypes in driving suspicions is also emphasised within the reports. It is suggested that this key characteristic has more dominance in CMC than it would do face-to-face because of the occlusion of the traditional nonstrategic clues to deceit. Evidence for an alternative set of nonstrategic leakage clues was examined further by conducting a variant of the Guilty-Knowledge test within the context of a CMC based crime. It was found that participants exhibited a response time inhibition effect when presented with 'guilty knowledge' and that this effect was detectable through a standard two-button mouse. The use of such nonstrategic cues to deceit was explored further in a study that examined how CMC might be used to add additional control to a Statement Validity Assessment truth-validation test. It was found that the content analysis technique used by SVA was unable in its present form to correctly distinguish between truthful and fabricated statements of participants interviewed using a CMC chat program. In addition, it was found that the deletion-behaviours of participants fabricating a story within CMC provided no quantitative or qualitative evidence that they were lying

Instructing jurors on detecting deception: is the jury still out?

This thesis established the importance of understanding deception in courtrooms, demonstrating that expert evidence can achieve immediate and long-term benefits by correcting jurors’ biases and misconceptions around flawed stereotypes of deception. Improvements found indicate that psychological evidence can protect jurors from relying on misplaced common sense when assessing witness credibility

Video Collaboration: Copresence and Performance

The purpose of this qualitative narrative theory study on video collaboration platform use is to explain how an individual\u27s on-screen performance and their interpersonal verbal and nonverbal communication contributes to engagement and copresence with their audience. The literature review analyzes critical interpersonal communication theories to explain how this affects engagement and copresence levels in mediated virtual environments. The research was conducted through interviews with thirty professional businesspeople about their video collaboration experiences during the COVID-19 2020 shutdown. The interview respondents told the stories of business communication successes and failures that correspond to the scholarly theories in the literature review. The respondents discussed how verbal and nonverbal communication was used successfully and unsuccessfully. They also discussed why their companies found it challenging to communicate virtually during the COVID-19 shutdown with video collaboration. A final discussion analyzes how communication theory and practical experience combined to explain how verbal and nonverbal communication impact mediated virtual communications when using video collaboration. This study offers a model to help explain how interpersonal communication, engagement, and copresence exist in a cyclical motion. This model can be helpful to business people and scholars to communicate in a mediated virtual environment using video collaboration platforms

High-Tech Dispute Resolution: Lessons from Psychology for a Post-Covid-19 Era

Covid-19 fostered a remote technology boom in the world of dispute resolution. Pre-pandemic, adoption of technical innovation in dispute resolution was slow moving. Some attorneys, courts, arbitrators, mediators and others did use technology, including telephone, e-mail, text, or videoconferences, or more ambitious online dispute resolution (ODR). But, to the chagrin of technology advocates, many conducted most dispute resolution largely in-person. The pandemic effectively put the emerging technological efforts on steroids. Even the most technologically challenged quickly began to replace in-person dispute resolution with videoconferencing, texting, and other technology. Courts throughout the world canceled all or most in-person trials, hearings, conferences, and appeals and began to experiment with using technologically-assisted alternatives. The U.S. Supreme Court held oral arguments using telephone conference calls. Attorneys, mediators, and arbitrators relied far more heavily on phone, e-mail, text, and video. Some courts expanded programs to help disputants obtain information and even resolve their disputes online. “Thanks” to the pandemic, the traditionally slow-moving and technology-resistant legal community suddenly embraced many kinds of technology with both arms and more. This move to technology-mediated dispute resolution was met with greater enthusiasm than many might have anticipated, leading to predictions that we may never return to the world of extensive reliance on in-person dispute resolution. As the pandemic endured, lawyers, neutrals, and court administrators found that practices adopted out of desperation could be worth preserving post-pandemic. Michigan Supreme Court Chief Justice Bridget Mary McCormack, in describing “temporary” pandemic adjustments, noted: “I don’t think that things will ever return to the way they were, and I think that is a good thing.” Even many who were previously hesitant about or relatively unaware of the possible uses of technology saw the potential for clear benefits. Some judges, mediators, arbitrators, and court administrators observed that the online versions of litigation, mediation, and arbitration could be as good or even better than the in-person versions. Some began to consider new ways to combine processes or to use them differently. Tech advocates saw this as one silver lining of the pandemic, noting that Covid-19 achieved a result that twenty years of tech advocacy could not. As in-person interactions once again become possible, disputants, lawyers, courts, and neutrals will need to decide whether and under what circumstances to conduct interviews, depositions, court proceedings, negotiations, mediations, or arbitrations in-person, by phone, using videoconferencing, or in writing of some form. While many hail the potential benefits of using technology, others fear the loss of the human side of dispute resolution, expressing significant skepticism that technology can adequately replace the close contact, credibility assessment, rapport, and interpersonal connection they believe are critically important aspects of dispute resolution. Some tout the possibilities for using technology to facilitate access to justice, but others worry about the ways that technology might impede such access. Psychological science provides a useful lens through which to consider these essential issues. Using different means of communication can influence how participants experience the interaction and these experiential differences have important implications for dispute resolution. These implications offer valuable lessons for legal actors choosing which modes of communication to use and determining how to communicate well within a particular medium. While it is natural to seek simple answers, the psychological research we explore is nuanced, revealing that no single mode of communication is “best” in all circumstances. In lieu of a simple solution we provide a multi-dimensional analysis that will help guide decision makers in making these critical determinations. Understanding the science will help participants maximize the benefits and minimize the drawbacks of different communication media, enabling them to make informed choices among media, design the chosen media to fit their goals, and adjust their advocacy, judging, negotiation, and other activities to the chosen medium. In Section II, we draw on psychology to analyze four key characteristics of communication media: (1) the channels that they provide for communication, (2) the degree to which they facilitate synchronous or asynchronous communication; (3) the extent to which they provide transparency or privacy; and (4) their formality, familiarity, and accessibility. In Section III, we explore how these characteristics affect participants in dispute resolution. We focus on the impacts of alternative modes of communication in ten areas that are particularly relevant to dispute resolution: (1) focus and fatigue; (2) rapport; (3) emotion; (4) the exchange of information; (5) participant behavior; (6) credibility determinations; (7) persuasion; (8) judgment and decision making; (9) procedural justice; and (10) public views of justice. In Section IV, we explore how decision makers might incorporate the insights of psychology into their technological choices. We identify three important variables for decision makers to consider: the goals the decision maker has for the process; the characteristics of the disputants; and the nature of the dispute or task. We explain why these variables are critically important and provide examples of how decision makers can draw on psychology to best fulfill their goals in designing and using technology for dispute resolution. In Section V, we briefly conclude and point to several areas in which additional research would be particularly useful

Suspicion Modeling in Support of Cyber-Influence Operations/Tactics

Understanding the cognitive process of IT user suspicion may assist organizations in development of network protection plans, personnel training, and tools necessary to identify and mitigate nefarious intrusions of IT systems. Exploration of a conceptual common ground between psycho-social and technology-related concepts of suspicion are the heart of this investigation. The complexities involved in merging these perspectives led to the overall research question: What is the nature of user suspicion toward IT: The research problem/phenomenon was addressed via extensive literature review, and use of the Interactive Qualitative Analysis problem/phenomenon. Analysis of the system led to the development of a model of IT suspicion as a progenitor for future experimental constructs that measure or assess behavior as a result of cyber attacks

The influence of micro-expressions on deception detection

Facial micro-expressions are universal symbols of emotions that provide cohesion to interpersonal communication. At the same time, the changes in micro-expressions are considered to be the most important hints in the psychology of emotion. Furthermore, analysis and recognition of these micro-expressions have pervaded in various areas such as security and psychology. In security-related matters, micro-expressions are widely used to detect deception. In this research, a deep learning model that interprets the changes in the face into meaningful information has been trained using The Facial Expression Recognition 2013 dataset. Necessary data is also obtained through live stream or video stream by detecting via computer vision and evaluating with the trained model. Finally, the data obtained is transformed into graphic and interpreted to determine whether the people are trying to deceive or not. The deception classification accuracy of the custom trained model is 74.17% and the detection of the face with high precision using the computer vision methods increased the accuracy of the obtained data and provided it to be interpreted correctly. In this respect, the study differs from other studies using the same dataset. In addition, it is aimed to facilitate the deception detection which is performed in a complex and expensive way, by making it simple and understandable