Michael Pardo and Dennis Patterson have recently put forward several provocative and stimulating criticisms that strike at the heart of much work that has been done at the crossroads of neuroscience and the law. My goal in this essay is to argue that their criticisms of the nascent but growing field of neurolaw are ultimately based on questionable assumptions concerning the nature of the ever evolving relationship between scientific discovery and ordinary language. For while the marriage between ordinary language and (...) scientific discovery is admittedly not always a happy one, it is an awkward union that nevertheless seems to work itself out with the passage of time. In the following pages, I will try to show that Pardo and Patterson’s primary argumentative strategy ultimately depends on basic assumptions concerning the fixity of language that we should reject. (shrink)

Detection of deception and confirmation of truth telling with conventional polygraphy raised a host of technical and ethical issues. Recently, newer methods of recording electromagnetic signals from the brain show promise in permitting the detection of deception or truth telling. Some are even being promoted as more accurate than conventional polygraphy. While the new technologies raise issues of personal privacy, acceptable forensic application, and other social issues, the focus of this paper is the technical limitations of the developing (...) technology. Those limitations include the measurement validity of the new technologies, which remains largely unknown. Another set of questions pertains to the psychological paradigms used to model or constrain the target behavior. Finally, there is little standardization in the field, and the vulnerability of the techniques to countermeasures is unknown. Premature application of these technologies outside of research settings should be resisted, and the social conversation about the appropriate parameters of its civil, forensic, and security use should begin. (shrink)

Detection of deception and confirmation of truth telling with conventional polygraphy raised a host of technical and ethical issues. Recently, newer methods of recording electromagnetic signals from the brain show promise in permitting the detection of deception or truth telling. Some are even being promoted as more accurate than conventional polygraphy. While the new technologies raise issues of personal privacy, acceptable forensic application, and other social issues, the focus of this paper is the technical limitations of the developing (...) technology. Those limitations include the measurement validity of the new technologies, which remains largely unknown. Another set of questions pertains to the psychological paradigms used to model or constrain the target behavior. Finally, there is little standardization in the field, and the vulnerability of the techniques to countermeasures is unknown. Premature application of these technologies outside of research settings should be resisted, and the social conversation about the appropriate parameters of its civil, forensic, and security use should begin. (shrink)

Although lie detection procedures have been fundamentally criticized since their inception at the beginning of the 20th century, they are still in use around the world. In addition, they have created some remarkable appeal in the context of counterterrorism policies. Thereby, the links between science and fiction in this topic are quite tight and by no means arbitrary: In the progressive narrative of the lie detection devices, there is a promise of changing society for the better, which is (...) entangled in a fictional narrative provided by many cinematic and literary examples. By drawing on the concept of “diegetic technologies” formulated by David Kirby, we want to highlight the role of science fictional narratives in the historical development and current application of lie detection procedures. We therefore aim to use this conceptual frame to analyze the role of prevention-oriented mind reading procedures, which are developed for or already used in the “war on terror” with reference to their fictional predecessors. One virulent factor has to be highlighted in this context: The fictional engagement with possible new lie detection practices is in itself creating a legitimating ground for future security technologies. (shrink)

The biological function of human reasoning abilities cannot be to improve shared knowledge. This is at best a side effect. A more plausible function of argumentation, and thus of reasoning, is to advertise one's ability to detect lies and errors. Such selfish behavior is closer to what we should expect from a naturally selected competence.

Chris N. H. Street Behavioral and Social Sciences Department, University of Huddersfield, UK We are very inaccurate lie detectors, and … Read More →.

The lie detector test has long been treated with suspicion by the law. Recently, several authors have called this suspicion into question. They argue that the lie detector test may have considerable forensic benefits, particularly if we move past the classic, false-positive prone, autonomic nervous system-based (ANS-based) control question test, to the more reliable, brain-based, concealed information test. These authors typically rely on a “comparative advantage” argument to make their case. According to this argument, we should not be so suspicious (...) of lie detection evidence if it has comparative advantages over the epistemic methods currently utilised by the legal system. In this article, I add to this growing support by making a novel comparative advantage argument in favour of brain-based lie detection evidence. The argument focuses on the P300 concealed information test (P300 CIT), which has several unique properties, and on the effect it may have on pre-trial bargaining in criminal cases rather than in-court evidence. The thesis is that P300 CIT could allow for innocent defendants to credibly signal their innocence to investigators and prosecutors during pre-trial bargaining more effectively than current proposed methods for doing the same thing. I defend this argument from a number of objections, and suggest that it opens up an interesting avenue in the ongoing debate about the merits of this technology. Although the argument is presented with the criminal law in mind, it could form part of a more general cumulative case in favour of this technology. (shrink)

This article analyzes emerging artificial intelligence (AI)-enhanced lie detection systems from ethical and human resource (HR) management perspectives. I show how these AI enhancements transform lie detection, followed with analyses as to how the changes can lead to moral problems. Specifically, I examine how these applications of AI introduce human rights issues of fairness, mental privacy, and bias and outline the implications of these changes for HR management. The changes that AI is making to lie detection are (...) altering the roles of human test administrators and human subjects, adding machine learning-based AI agents to the situation and establishing invasive data collection processes as well as introducing certain biases in results. I project that the potentials for pervasive and continuous lie detection initiatives (“truth machines”) are substantial, displacing human-centered efforts to establish trust and foster integrity in organizations. I argue that if it is possible for HR managers to do so, they should cease using technologically-based lie detection systems entirely and work to foster trust and accountability on a human scale. However, if these AI-enhanced technologies are put into place by organizations by law, agency mandate, or other compulsory measures, care should be taken that the impacts of the technologies on human rights and wellbeing are considered. The article explores how AI can displace the human agent in some aspects of lie detection and credibility assessment scenarios, expanding the prospects for inscrutable, “black box” processes and novel physiological constructs (such as “biomarkers of deceit”) that may increase the potential for such human rights concerns as fairness, mental privacy, and bias. Employee interactions with autonomous lie detection systems rather with than human beings who administer specific tests can reframe organizational processes and rules concerning the assessment of personal honesty and integrity. The dystopian projection of organizational life in which analyses and judgments of the honesty of one’s utterances are made automatically and in conjunction with one’s personal profile provides unsettling prospects for the autonomy of self-representation. (shrink)

Detection of deception and confirmation of truth telling with conventional polygraphy raised a host of technical and ethical issues. Recently, newer methods of recording electromagnetic signals from the brain show promise in permitting the detection of deception or truth telling. Some are even being promoted as more accurate than conventional polygraphy. While the new technologies raise issues of personal privacy, acceptable forensic application, and other social issues, the focus of this paper is the technical limitations of the developing (...) technology. Those limitations include the measurement validity of the new technologies, which remains largely unknown. Another set of questions pertains to the psychological paradigms used to model or constrain the target behavior. Finally, there is little standardization in the field, and the vulnerability of the techniques to countermeasures is unknown. Premature application of these technologies outside of research settings should be resisted, and the social conversation about the appropriate parameters of its civil, forensic, and security use should begin. (shrink)

People are typically poor at telling apart truthful and deceptive statements. Based on the Unconscious Thought Theory, it has been suggested that poor lie detection arises from the intrinsic limitations of conscious thinking and can be improved by facilitating the contribution of unconscious thought. In support of this hypothesis, Reinhard, Greifeneder, and Scharmach (2013) observed improved lie detection among participants engaging in unconscious thought. The present study aimed to replicate this unconscious thought advantage using a similar experimental procedure (...) but with an important improvement in a key control condition. Specifically, participants judged the truthfulness of 8 video recordings in three thinking modes: immediately after watching them or after a period of unconscious or conscious deliberation. Results from two experiments (combined N = 226) failed to reveal a significant difference in lie detection accuracy between the thinking modes, even after efforts were made to facilitate the occurrence of an unconscious thought advantage in Experiment 2. The results imply that the unconscious thought advantage in deception detection is not a robust phenomenon. (shrink)

In this paper, I argue that companies who use functional Magnetic Resonance Imaging (fMRI) scans for lie detection encounter the same basic ethical stumbling blocks as commercial companies that market traditional polygraphs. Markets in traditional voluntary polygraphs are common and fail to elicit much uproar among ethicists. Thus, for consistency, if markets in polygraphs are ethically unproblematic, markets using fMRIs for lie detection are equally as acceptable. Furthermore, while I acknowledge two substantial differences between the ethical concerns involving (...) polygraphs and fMRI lie detection, I argue that these concerns can be overcome and do not lead to the conclusion that markets in fMRI lie detection are ethically dubious. It is my conclusion that voluntary markets in fMRI lie detection can be justified by consumer autonomy and should be allowed to persist. (shrink)

Can managers detect honest people’s lies in a handwritten message? In this article, I will briefly discuss graphology and a basic model of interpersonal communication. I will then develop a fundamental theoretical framework of eight principles for detecting lies based on the basic communication model, handwriting analyses, and the following assumptions: For most people, it is easier to tell the truth than to tell lies. This applies to handwritings also. When most honest people lie, they try to hide their stressful (...) emotions in the encoding process. As a consequence, they deviate from their own normal writing and violate their own personal moral standards. Interestingly enough, the art or science of detecting a lie in a handwritten sample is to focus not on what they write, but on how they write it. These 24 exhibits (cases) written in 11 languages—used in different parts of the world—help managers apply this important theoretical framework of interpersonal communication, understand the encoding process, pinpoint these sudden emotional changes, decode handwritten messages, unlock the secrets, reveal the message’s true meanings, and detect people’s lies. (shrink)

A growing literature has focused on understanding how to detect and deter unethical consumer behavior. In this work, we focus on a particularly important type of unethical consumer behavior, consumer insurance fraud, and we analyze a unique dataset to understand how experts investigate suspicious claims. Two separate but related literatures inform the process of investigating suspicious insurance claims. The first literature is grounded in field research and emphasizes the importance of secondary sources. The second literature is grounded in laboratory studies (...) that emphasize the importance of interpersonal interactions. Here we draw upon both literatures to consider the importance of claimant interviews within the context of many investigative actions and the potential for claimants to avoid interviews. In an empirical study using qualitative and quantitative data from auto insurance claim investigations, we analyze investigative chronologies conducted by skilled experts. In doing so, we find that even when investigators can access information from a variety of sources such as witnesses, databases, and physical evidence, claimant interviews are the most important step in determining whether or not claims are denied or paid. Furthermore, we identify interpersonal avoidance as an important signal of unethical claimant behavior. Our findings inform deception detection theory and practice. We identify implications for deception detection in business, particularly for consumer unethical behavior and insurance fraud investigations. (shrink)

A growing literature has focused on understanding how to detect and deter unethical consumer behavior. In this work, we focus on a particularly important type of unethical consumer behavior, consumer insurance fraud, and we analyze a unique dataset to understand how experts investigate suspicious claims. Two separate but related literatures inform the process of investigating suspicious insurance claims. The first literature is grounded in field research and emphasizes the importance of secondary sources. The second literature is grounded in laboratory studies (...) that emphasize the importance of interpersonal interactions. Here we draw upon both literatures to consider the importance of claimant interviews within the context of many investigative actions and the potential for claimants to avoid interviews. In an empirical study using qualitative and quantitative data from auto insurance claim investigations, we analyze investigative chronologies conducted by skilled experts. In doing so, we find that even when investigators can access information from a variety of sources such as witnesses, databases, and physical evidence, claimant interviews are the most important step in determining whether or not claims are denied or paid. Furthermore, we identify interpersonal avoidance as an important signal of unethical claimant behavior. Our findings inform deception detection theory and practice. We identify implications for deception detection in business, particularly for consumer unethical behavior and insurance fraud investigations. (shrink)

Geven, Ben‐Shakhar, Kindt and Verschuere point out that research on deception detection usually employs instructed cheating. They experimentally demonstrate that participants show slower reaction times for concealed information than for other information, regardless of whether they are explicitly instructed to cheat or whether they can freely choose to cheat or not. Finding this ‘cognitive signature of lying’ with self‐initiated cheating too is argued by the authors to strengthen the external validity of deception detection research. [75].

The pervasiveness of lying -- Why the lie? The reasons and justifications for lying -- How and why different types of people lie -- Taking the Lie-Q test : learning where you fit -- Everyday social lies -- Lying in public -- Lying at work -- Lying in business -- Lying to friends & relatives -- When men & women lie-the dating game -- Lies with husbands, wives, & intimate others -- The lies of parents & children -- Lying to (...) oneself -- The strategy of deceiving and perceiving (or how to detect when someone is lying) -- Conclusion (or how to deal with different kinds of lies and liars). (shrink)

The standard view in social science and philosophy is that lying does not require the liar’s assertion to be false, only that the liar believes it to be false. We conducted three experiments to test whether lying requires falsity. Overall, the results suggest that it does. We discuss some implications for social scientists working on social judgments, research on lie detection, and public moral discourse.

Atran & Norenzyan (A&N) claim that an appreciation of the evolved inferential machinery underlying supernatural beliefs can greatly aid us in understanding regularities in culturally shared conceptions of religion. I explore how their model provides insight into why culturally shared tales of horror (e.g., horror movies) often combine religious and predatory content.

Detection theory has been applied to a host of varied problems (for example, measuring the accuracy of diagnostic systems or reliability of lie detection tests) and extends far beyond the detection of signals. This book is a primer on the subject.

Recent developments in AI, especially the spectacular success of Large Language models, have instigated renewed questioning of what remains distinctively human. As AI stands poised to take over more and more human tasks, what is left that distinguishes humans? One way we might identify a humanlike intelligence would be when we detect it telling lies. Yet AIs lack both the intention and the motivation to truly tell lies, instead producing merely bullshit. With neither emotions, embodiment, nor the social awareness that (...) leads to a theory of mind, AIs lack the internal referents on which to judge truth or falsity. When we are deceived by our computers, we need to look for the hidden agent who benefits from the deception. (shrink)

The ability to detect deception is one of the most intriguing features of our minds. Cognitive load can surprisingly increase the accuracy of detection when there is a substantial load compared to when the detection is performed without cognitive load. This effect was tested in two experiments. In the first experiment, the participants were asked to watch truth/lie videos while completing a concurrent task (N‐back in a 3‐back version; intuitive processing), providing verbal reasoning after watching each video (deliberative (...) processing), or watching the videos alone (control group). The cognitive load caused by the concurrent task led to a higher accuracy in deception detection compared to the other conditions. In the second experiment, we examined how this effect worked under various amounts of cognitive load. Participants watching truth/lie videos were assigned to one of three experimental conditions (N‐back in three versions: 1, 3, and 5‐back) or to a control group. The participants in the 3‐back and 5‐back conditions exhibited a significantly higher accuracy in deception detection than those in the 1‐back and control groups. Thus, the effect of increased accuracy in deception detection is due to cognitive load and is related to the amount of cognitive load present. (shrink)

Editors van Ditmarsch, Hendriks and Verbrugge of this special issue of topiCS on lying describe some recent trends in research on lying from a multidisciplinary perspective, including logic, philosophy, linguistics, psychology, cognitive science, behavioral economics, and artificial intelligence. Furthermore, they outline the seven contributions to this special issue.

Editors van Ditmarsch, Hendriks and Verbrugge of this special issue of topiCS on lying describe some recent trends in research on lying from a multidisciplinary perspective, including logic, philosophy, linguistics, psychology, cognitive science, behavioral economics, and artificial intelligence. Furthermore, they outline the seven contributions to this special issue.

Brain imaging studies suggest that truth telling constitutes the default of the human brain and that lying involves intentional suppression of the predominant truth response. By manipulating the truth proportion in the Sheffield lie test, we investigated whether the dominance of the truth response is malleable. Results showed that frequent truth telling made lying more difficult, and that frequent lying made lying easier. These results implicate that the accuracy of lie detection tests may be improved by increasing the dominance (...) of the truth response and that habitual lying makes the lie response more dominant. (shrink)

Compared to truthful answers, deceptive responses to queries are expected to take longer to initiate. Yet attempts to detect lies through reaction time (RT) have met with limited success. We describe a new procedure that seems to increase the RT difference between truth-telling and lies. It relies on a Stroop-like procedure in which responses to the labels true and false are sometimes reversed. The utility of this method is assessed in a laboratory study involving both statements of fact and attitude. (...) Three different ethnic groups participated: Americans of European ancestry, East Asians, and native Arabic speakers. For all three groups, our technique allowed identification of prevarication reliably better than chance. (shrink)

This book offers information about what constitutes dishonesty or lying and why it occurs. Based on the author's professional experiences as an attorney and a psychologist, he explains reasons why lying is a human frailty and offers guidance on how a person can detect lies, nip them in the bud, and maintain personal defenses against being treated in a harmful manner. The book is wrapped up with comments about how the control and elimination of influence from dishonest people enhances self-fulfillment, (...) and how this will lead to personal health, happiness, and positive social relationships. (shrink)

Deception is a reasonably common part of daily life that society sometimes demonstrates a degree of acceptance of, and occasionally people are very willing to be deceived. But can a computer identify deception and distinguish it from that which is not deceptive? We explore deception in various guises, differentiating it from lies, and highlighting the influence of medium and message in both deception and its detection. Our investigations to date have uncovered disagreements relating to the measurements of such cues, (...) and variations in interpretations, as could be problematic in building a deception detection system. (shrink)

What is the orienting response, and what does it have to do with narrative? How is narrative related to lying? And what is the motive force of narrative? What we shall see is that the mental activity of writers creating fictions, readers reading them, liars fashioning lies, and listeners when they detect a lie, all share distinct and significant cognitive functions in common.

Memory Detection Tests (MDTs) are a general class of psychophysiological tests that can be used to determine whether someone remembers a particular fact or datum. The P300 MDT is a type of MDT that relies on a presumed correlation between the presence of a detectable neural signal (the P300 “brainwave”) in a test subject, and the recognition of those facts in the subject’s mind. As such, the P300 MDT belongs to a class of brain-based forensic technologies which have proved (...) popular and controversial in recent years. With such tests increasingly being proffered for use in the courtroom — to either support or call into question testimony — it would behoove the legal system to have some systematic framework for ensuring that they are used responsibly. In this paper, I defend one such framework for ensuring that this is the case: the legitimacy enhancing test. According to this test, it is appropriate to make use of technologies such as the P300 MDT whenever doing so would (probably) enhance the legitimacy of the trial. I argue that this test addresses tensions between scientific and legal norms of evidence, and exhibits a number of additional virtues including unification, simplicity and flexibility. Although the test is defended by considering the example of the P300 MDT, its significance is much broader than that. If it has the virtues I claim for it, it should provide a general framework for the responsible use of technologies, and the responsible innovation of social epistemic systems. (shrink)

Research in the psychology of deception detection implies that Fricker, in making her case for reductionism in the epistemology of testimony, overestimates both the epistemic demerits of the antireductionist policy of trusting speakers blindly and the epistemic merits of the reductionist policy of monitoring speakers for trustworthiness: folk psychological prejudices to the contrary notwithstanding, it turns out that monitoring is on a par (in terms both of the reliability of the process and of the sensitivity of the beliefs that (...) it produces) with blind trust. The consequence is that while (a version of) Fricker’s argument for the necessity of a reduction succeeds, her argument for the availability of reductions fails. This does not, however, condemn us to endorse standard pessimistic reductionism, according to which there is no testimonial knowledge, for recent research concerning the methods used by subjects to discover deception in non-laboratory settings suggests that only a more moderate form of pessimism is in order. (shrink)

Social attention is thought to require detecting the eyes of others and following their gaze. To be effective, observers must also be able to infer the person's thoughts and feelings about what he or she is looking at, but this has only rarely been investigated in laboratory studies. In this study, participants' eye movements were recorded while they chose which of four patterns they preferred. New observers were subsequently able to reliably guess the preference response by watching a replay of (...) the fixations. Moreover, when asked to mislead the person guessing, participants changed their looking behavior and guessing success was reduced. In a second experiment, naïve participants could also guess the preference of the original observers but were unable to identify trials which were lies. These results confirm that people can spontaneously use the gaze of others to infer their judgments, but also that these inferences are open to deception. (shrink)

Role-based database management systems are most widely used for information storage and analysis but are known as vulnerable to insider attacks. The core of intrusion detection lies in an adaptive system, where an insider attack can be judged if it is different from the predicted role by performing classification on the user’s queries accessing the database and comparing it with the authorized role. In order to handle the high similarity of user queries for misclassified roles, this paper proposes a (...) deep metric neural network with strategic sampling algorithm that properly extracts salient features and directly learns a quantitative measure of similarity. A strategic sampling method of heuristically generating and learning training pairs through Monte Carlo search is proposed to select a training pair that can represent the entire dataset. With the TPC-E–based benchmark data trained with 11,000 queries for 11 roles, the proposed model produces the classification accuracy of 95.41%, which is the highest compared with the previous models. The results are verified through comparison of quantitative and qualitative evaluations, and the feature space modelled in the neural network is analysed by t-SNE algorithm. (shrink)

Introduction -- Fraud in research : frequency patterns -- An organizational approach to research fraud -- Fraud, lies, deceptions, fabrications, and falsifications -- Deviance in scientific research : norms, hot spots, control -- Concluding discussion.