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)

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.

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.

According to our folk theory of lying, liars leak observable cues of their insincerity, observable cues that make it easy to catch a liar in real time. Various prominent social epistemologists rely on the correctness of our folk theory as empirically well-confirmed when building their normative accounts of the epistemology of testimony. Deception detection research in communication studies, however, has shown that our folk-theory is mistaken. It is not empirically well-confirmed but empirically refuted. Michaelian (2010) and Shieber (2012) have (...) already discussed some of this literature and its relevance for epistemology, especially for the most worked out reliance on our folk theory by Elizabeth Fricker (1994, 2016, 2017a, 2024). Fricker (2016) raises a reasonable objection to their presentations of the research: is the research ecologically valid? Do the experiments in the lab carry over to real life? This chapter conveys the methodology of the research, defends its ecological validity, and addresses further research on the nature and frequency of lies in ordinary life. Social epistemologists stand to gain from understanding the nuts and bolts of deception detection research and its findings. The chapter concludes with a detailed examination of Fricker’s relilance on folk theory in her “local reductionist” epistemology of testimony. Further areas of research relevant to social epistemology are listed. (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.

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)

A fundamental challenge in virology research lies in effectively detecting malicious code. N-gram analysis has become a cornerstone technique, but selecting the most informative features, especially for longer n-grams, remains crucial for efficient detection. This paper addresses this challenge by introducing a novel feature extraction method that leverages both adjacent and non-adjacent bi-grams, providing a richer set of information for malicious code identification. Additionally, we propose a computationally efficient feature selection approach that utilizes a genetic algorithm combined with Boosting (...) principles. Our experimental results show that this detection system significantly outperforms existing methods in virus detection accuracy. The system improves detection accuracy by 15% and reduces false positives by 20% compared to traditional n-gram techniques. Additionally, it cuts computational overhead by about 30%, making it suitable for real-time applications. These advancements demonstrate the effectiveness and practicality of our approach. Future research will focus on applying our methods to polymorphic viruses and other malware to further enhance their robustness and applicability. (shrink)

Abstract: Early detection of breast cancer plays a pivotal role in improving patient prognosis and reducing mortality rates. Recent technological advancements have significantly enhanced the accuracy and effectiveness of breast cancer screening methods. This paper explores the latest innovations in early detection, including the evolution of digital mammography, the impact of 3D mammography (tomosynthesis), and the use of advanced imaging techniques such as molecular imaging and MRI. Furthermore, the integration of artificial intelligence (AI) in diagnostic tools is discussed, (...) highlighting how machine learning algorithms are refining imaging analyses and reducing diagnostic errors. Advances in genetic screening, liquid biopsies, and biomarkers are also examined, showcasing their potential in identifying high-risk individuals and enabling personalized treatment plans. This paper provides insights into the future of breast cancer detection, outlining both the opportunities and challenges that lie ahead in adopting these innovative technologies to improve patient outcomes. (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)

Deepfakes pose a multi-faceted threat to the acquisition of knowledge. It is widely hoped that technological solutions—in the form of artificially intelligent systems for detecting deepfakes—will help to address this threat. I argue that the prospects for purely technological solutions to the problem of deepfakes are dim. Especially given the evolving nature of the threat, technological solutions cannot be expected to prevent deception at the hands of deepfakes, or to preserve the authority of video footage. Moreover, the success of such (...) technologies depends on institutional trust that is in short supply. Finally, outsourcing the discrimination between the real and the fake to automated, largely opaque systems runs the risk of undermining epistemic autonomy. (shrink)

In modern days, person-computer communication systems have gradually penetrated our lives. One of the crucial technologies in person-computer communication systems, Speech Emotion Recognition (SER) technology, permits machines to correctly recognize emotions and greater understand users' intent and human-computer interlinkage. The main objective of the SER is to improve the human-machine interface. It is also used to observe a person's psychological condition by lie detectors. Automatic Speech Emotion Recognition(SER) is vital in the person-computer interface, but SER has challenges for accurate recognition. (...) In this work to resolve the above problem, automatic Speech enhancement shows that deep learning techniques effectively eliminate background noise. Using Deep leaning models for four states were created: happy, sad, angry, and intoxicated. Recurrent Neural Network (RNN) algorithm used to reduce the possibility of over fitting by randomly omitting neurons in the hidden layers. The proposed RNN method could be implemented in personal assistant systems to give better and more appropriate state-based interactions between humans. In the simulation results shows Improving accuracy, Time complexity, Error rate is also reduced to using the proposed method. -/- . (shrink)

Rawlsian political liberalism famously requires a prohibition on truth. This has led to the charge that liberalism embraces non-cognitivism, according to which political claims have the moral status of emotions or expressions of preference. This result would render liberalism a non-starter for liberatory politics, a conclusion that political liberals themselves disavow. This conflict between what liberalism claims and what liberalism does has led critics to charge that the theory is disingenuous and functions as political ideology. In this paper, I explore (...) one way that this charge unfolds: critics charge that liberalism utilizes an individualistic and identity-insensitive social ontology, which in turn yields epistemic deficiencies that render it incapable of detecting oppression. The theory’s claim to freestandingness then shields it from necessary critique. I argue that this objection relies on constructing a conflict between liberalism’s professed non-cognitivism and its actual cognitivist commitments. By demonstrating that Rawlsian political liberalism explicitly endorses substantive moral truths, and that the method of avoidance applies only to public justification for coercive state action, I show that the theory is openly and foundationally cognitivist, and thus that the charge of disingenuousness does not stick. (shrink)

Advancements in cloud technologies have increased the infrastructural needs of data centers due to storage needs and processing of extensive dimensional data. Many service providers envisage anomaly detection criteria to guarantee availability to avoid breakdowns and complexities caused due to large-scale operations. The streaming log data generated is associated with multi-dimensional complexity and thus poses a considerable challenge to detect the anomalies or unusual occurrences in the data. In this research, a hybrid model is proposed that is motivated by (...) deep belief criteria and meta-heuristics. Using Search-and-Rescue—BrainStorm Optimization (SAR-BSO), a hybrid feature selection (FS) and deep belief network classifier is used to localize and detect anomalies for streaming data logs. The significant contribution of the research lies in FS, which is carried out using SAR-BSO which increases the detection power of the model as it selects the most significant variables by minimizing redundant features. The evaluation of accuracy is efficiently improved when compared with the predictable methods, such as Extract Local Outlier Factor (ELOF), Track-plus, Hybrid Distributed Batch Stream (HDBS), IForestASD, DBN, BSO-based Feature Selection with DBN, Genetic Algorithm-Deep Belief Network (GA-DBN), Mutual Information-Deep Belief Network (MI-DBN), information entropy-Deep Belief Network(I + DBN), Flat Field-Deep Belief Network (FF + DBN), African Vulture Optimization Algorithm-Deep Belief Network(AVOA + DBN), Gorilla Troop Optimizer-Deep Belief Network(GTO-DBN), and SARO-based Feature Selection with DBN. Further, the accurate detection of the anomalies in the data stream is established by the Deep Belief Neural Network (DBN) classifier. The model’s efficacy is determined using Apache, Hadoop, HDFS, Spark, and Linux datasets and evaluated against existing similar models. The model efficiency is provided using multiple evaluation metrics and is found effective. From the experimentation, the accuracy of the proposed model is found to be 93.3, 95.4, 93.6, 94.2, and 93.5% respectively for the dataset such as Apache, Hadoop, HDFS, spark, and Linux. This enhancement in accuracy is due to the selection of optimal features by the proposed SAR-BSO algorithm. (shrink)

It could be argued that tort law is failing, and arguably an example of this failure is the recent public liability and insurance (‘PL&I’) crisis. A number of solutions have been proposed, but ultimately the chosen solution should address whatever we take to be the cause of this failure. On one account, the PL&I crisis is a result of an unwarranted expansion of the scope of tort law. Proponents of this position sometimes argue that the duty of care owed by (...) defendants to plaintiffs has expanded beyond reasonable levels, such that parties who were not really responsible for another’s misfortune are successfully sued, while those who really were to blame get away without taking any responsibility. However people should take responsibility for their actions, and the only likely consequence of allowing them to shirk it is that they and others will be less likely to exercise due care in the future, since the deterrents of liability and of no compensation for accidentally self-imposed losses will not be there. Others also argue that this expansion is not warranted because it is inappropriately fueled by ‘deep pocket’ considerations rather than by considerations of fault. They argue that the presence of liability insurance sways the judiciary to award damages against defendants since they know that insurers, and not the defendant personally, will pay for it in the end anyway. But although it may seem that no real person has to bear these burdens when they are imposed onto insurers, in reality all of society bears them collectively when insurers are forced to hike their premiums to cover these increasing damages payments. In any case, it seems unfair to force insurers to cover these costs simply because they can afford to do so. If such an expansion is indeed the cause of the PL&I crisis, then a contraction of the scope of tort liability, and a pious return to the fault principle, might remedy the situation. However it could also be argued that inadequate deterrence is the cause of this crisis. On this account the problem would lie not with the tort system’s continued unwarranted expansion, but in the fact that defendants really have been too careless. If prospective injurers were appropriately deterred from engaging in unnecessarily risky activities, then fewer accidents would ever occur in the first place, and this would reduce the need for litigation at its very source. If we take this to be the cause of tort law’s failure then our solution should aim to improve deterrence. Glen Robinson has argued that improved deterrence could be achieved if plaintiffs were allowed to sue defendants for wrongful exposure to ongoing risks of future harm, even in the absence of currently materialized losses. He argues that at least in toxic injury type cases the tortious creation of risk [should be seen as] an appropriate basis of liability, with damages being assessed according to the value of the risk, as an alternative to forcing risk victims to abide the outcome of the event and seek damages only if and when harm materializes. In a sense, Robinson wishes to treat newly-acquired wrongful risks as de-facto wrongful losses, and these are what would be compensated in liability for risk creation (‘LFRC’) cases. Robinson argues that if the extent of damages were fixed to the extent of risk exposure, all detected unreasonable risk creators would be forced to bear the costs of their activities, rather than only those who could be found responsible for another’s injuries ‘on the balance of probabilities’. The incidence of accidents should decrease as a result of improved deterrence, reduce the ‘suing fest’, and so resolve the PL&I crisis. So whilst the first solution involves contracting the scope of tort liability, Robinson’s solution involves an expansion of its scope. However Robinson acknowledges that LFRC seems prima facie incompatible with current tort principles which in the least require the presence of plaintiff losses, defendant fault, and causation to be established before making defendants liable for plaintiffs’ compensation. Since losses would be absent in LFRC cases by definition, the first evidentiary requirement would always be frustrated, and in its absence proof of defendant fault and causation would also seem scant. If such an expansion of tort liability were not supported by current tort principles then it would be no better than proposals to switch accident law across to no-fault, since both solutions would require comprehensive legal reform. However Robinson argues that the above three evidentiary requirements could be met in LFRC cases to the same extent that they are met in other currently accepted cases, and hence that his solution would therefore be preferable to no-fault solutions as it would only require incremental but not comprehensive legal reform. Although I believe that actual losses should be present before allowing plaintiffs to seek compensation, I will not present a positive argument for this conclusion. My aim in this paper is not to debate the relative merits of Robinson’s solution as compared to no-fault solutions, nor to determine which account of the cause of the PL&I crisis is closer to the truth, but rather to find out whether Robinson’s solution would indeed require less radical legal reform than, for example, proposed no-fault solutions. I will argue that Robinson fails to show that current tort principles would support his proposed solution, and hence that his solution is at best on an even footing with no-fault solutions since both would require comprehensive legal reform. (shrink)

Philosophical reflection on the idea of progress is undergoing a recent revival, especially because of renewed interest in the broad implications of the theory of biological evolution and in its applicability to epistemology. In this paper, the main interest lies with the following two questions: What kind of word is ‘progress’? Does it refer to a process that can be detected empirically? In the first section, three ways of understanding biological progress are evaluated. It is shown that ambiguity arises in (...) each of these ways due to the arbitrary and inevbitable choice of evaluative criteria involved. The second section of the paper deals with cognitive progress. According to evolutionary epistemology, the picture we have of the world at any one time is less approximate than the ones we had before it. We are converging onto the correct description. Problems arise here because one must have, just as in the previous cases, a pre-established evaluative criterion. The third section of the paper draws some implications from these conclusions and applies them to the understanding of cultural and moral progress in the most general sense. The final section of the paper brings together the insights of the previous sections so as to highlight some logical features of the concept of progress that prevent its exhaustive analysis. (shrink)

At the heart of Mizrahi’s project lies a sociological narrative concerning the recent history of philosophers’ negative attitudes towards scientism. Critics (e.g. de Ridder (2019), Wilson (2019) and Bryant (2020)), have detected various empirical inadequacies in Mizrahi’s methodology for discussing these attitudes. Bryant (2020) points out one of the main pertinent methodological deficiencies here, namely that the mere appearance of the word ‘scientism’ in a text does not suffice in determining whether the author feels threatened by it. Not all philosophers (...) use the term in ‘inherently negative’ (29) or pejorative ways. In this paper, I not only corroborate Bryant’s critical claim, but argue that Mizrahi’s response to this part of Bryant’s objection is inadequate. (shrink)

This is one of the best popular cosmology books ever written and Guth is now (2016) a top physics Professor at MIT. He tells the extremely complex story of inflation and related areas of particle physics in such an absorbing style that it reads like a detective novel-in fact, it is a detective novel-how he and others found out how the universe started! The interweaving of his personal story and that of many colleagues along with their photos and many wonderfully (...) clear diagrams allows just the right amount of relaxation from the intensity of the physics. In places the style reminds one of Watson´s famous book ``The Double Helix``. He tells how his work on magnetic monopoles and spontaneous symmetry breaking led to the discovery of the inflationary theory of the very early universe (ca. 10 to minus 35 seconds!). -/- Along the way you will learn many gems that should stay with you a long time such as: the observed universe(e.g., everything the Hubble telescope etc. can see out to ca. 15 billion light years when the universe began) is likely just a vanishingly tiny part of the entire inhomogeneous universe which is about 10 to the 23rd times larger; the big bang probably took place simultaneously and homogeneously in our observed universe; there probably have been and will continue to be an infinite number of big bangs in an infinite number of universes for an infinite time; when a bang happens, everything(space, time, all the elements) from the previous universe are destroyed; the stretching of space can happen at speeds much greater than the speed of light; our entire observed universe lies in a single bubble out of an endless number so there may be trillions of trillions just in our own entire(pocket) universe(and there may be an endless number of such); none of these infinite number of universes interact-i.e., we can never find out anything about the others; each universe started with its own big bang and will eventually collapse to create a new big bang; all this implies that the whole universe is fractal in nature and thus infinitely regresses to ever more universes(which can lead one to thinking of it as a giant hologram); disagreements between the endless(hundreds at least) variations of inflation are sometimes due to lack of awareness that different definitions of time are being used; some theories suggest that there was a first big bang but we can never find out what happened before it; nevertheless it appears increasingly plausible that there was no beginning but rather an eternal cycle of the destruction and creation, each being the beginning of spacetime for that universe; to start a universe you need about 25g of matter in a 10 to minus 26cm diameter sphere with a false vacuum and a singularity(white hole). -/- He deliberately spends little time on the endless variants of inflation such as chaotic, expanded and supernatural inflation or on dark matter´, supersymmetry and string theory, though they were well known at the time as you can find by reading other books such as Michio Kaku´s `Hyperspace` (see my review) and countless others. Of course much has happened since this book appeared but it still serves as an excellent background volume so cheap now it’s free for the cost of mailing. -/- Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle’ 2nd ed (2019). Those interested in more of my writings may see ‘Talking Monkeys--Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet--Articles and Reviews 2006-2019 3rd ed (2019), The Logical Structure of Human Behavior (2019), and Suicidal Utopian Delusions in the 21st Century 4th ed (2019). (shrink)

Dans le diagnostic du cancer, la précocité du diagnostic est généralement un élément valorisé. Selon la croyance commune, un cancer détecté tôt aura plus de chance d’être traitable. Or, cette conception des avantages du diagnostic précoce mène dans certains cas au phénomène de surdiagnostic, soit le fait de diagnostiquer un cancer à des individus qui n’en ont pas encore un et qui sont potentiellement en voie de le développer. Dans cet article, nous défendrons d’abord que le phénomène de surdiagnostic est (...) lié en majeure partie à notre connaissance grandissante du cancer, et au fait que ces nouvelles connaissances causent des biais dans les processus de dépistage, conduits en vue de trouver un cancer. Afin de remédier à cette problématique, nous tenterons de montrer que le fait de simplement modifier notre approche du cancer et le vocabulaire médical associé permettrait de réduire les cas de surdiagnostics. (shrink)

Abstract: This research focuses on utilizing Artificial Neural Networks (ANNs) to predict Audit Risk accurately, a critical aspect of ensuring financial system integrity and preventing fraud. Our dataset, gathered from Kaggle, comprises 18 diverse features, including financial and historical parameters, offering a comprehensive view of audit-related factors. These features encompass 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' 'History_score,' 'score,' and 'Risk,' with a total of 774 samples. Our proposed neural network architecture, consisting of three (...) layers (1 input, 1 hidden, and 1 output), forms the core of this study. While it may seem simple, the power of ANNs lies not in complexity but in their ability to uncover intricate data patterns. The model underwent rigorous training and validation, resulting in remarkable outcomes—an accuracy of 100% and an average error rate of 0.000015. In addition to performance metrics, our research investigates feature importance, revealing the key contributors to Audit Risk prediction. Notably, 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' and 'History_score' emerged as the most influential factors, shedding light on the elements crucial for precise risk assessment. This study advances Audit Risk prediction models and highlights the potential of ANNs in strengthening financial system integrity and fraud prevention. The insights gained from our findings offer practical guidance for stakeholders in the audit and financial sectors. (shrink)

Este artigo pretende analisar três teorias a respeito do que é o objeto intencional da memória. As teorias abordadas são o realismo direto, o realismo representativo e o pragmatismo em filosofia da memória. A primeira delas defende que quando lembramos, acessamos um evento passado sem intermédios; a segunda argumenta que acessamos diretamente uma representação do evento passado; a última, elaborada recentemente, afirma que nossas lembranças são determinadas por nossas ações. Apresentamos a ideia central de cada teoria, com quais outras teorias (...) sobre a memória elas relacionam e as principais objeções que enfrentam. Após isso, demonstramos a nossa posição, qual seja, o realismo representativo nos parece a alternativa mais viável entre as opções atuais. (shrink)

What is the connection between dispositions and ethics? Some might think very little and those who are interested in dispositions tend to be metaphysicians whose interests are far from value. However, we argue in this paper that dispositions and dispositionality are central to ethics, indeed a precondition. Ethics rests on a number of notions that are either dispositional in nature or involve real dispositions or powers at work. We argue for a dispositional account of value that offers an alternative to (...) the traditional fact-value dichotomy. We explain the place of value within a structure that explains the possibility of ethics. Elsewhere in this structure, we argue that moral responsibility is a precondition for ethics and that it is a dispositional notion depending critically on what Mumford and Anjum have called the dispositional modality. Moral responsibility in turn depends on there being both agency and normativity. We argue that intentionality and agency are preconditions for agency and that value is a precondition of normativity. All these notions are dispositional and make best sense if there are real dispositions or causal powers of agents. (shrink)

A proposta deste trabalho é investigar a contribuição da filosofia de Henri Bergson para as discussões atuais sobre a memória. Atualmente, o debate concentra-se entre as teorias causalistas e as teorias simulacionistas acerca da memória. O primeiro grupo defende que entre a representação atual de uma experiência passada e esta experiência, há uma conexão causal. Por outro lado, o segundo grupo entende que a principal contribuição para as representações atuais a respeito de eventos passados surge das condições do momento presente, (...) dispensando a necessidade de uma relação entre a experiência e a representação atual. Henri Bergson, no final do século XIX, apresentou a memória como uma faculdade prática, cuja função é auxiliar na tomada de decisões a partir das informações adquiridas anteriormente. De modo que são as condições do sujeito no momento presente que indicarão quais lembranças serão evocadas. Os conteúdos destas lembranças não são idênticos aos conteúdos do momento em que foram apreendidos, pois as lembranças, na sua concepção, alteram-se ao longo do tempo conforme novas informações são obtidas. Até este ponto, parece haver uma grande aproximação entre a filosofia bergsoniana acerca da memória e a compreensão simulacionista. Contudo, Bergson também entende que a lembrança retida depende da percepção, ocasionando uma representação, que o sujeito teve no momento da experiência, afirmando a existência de uma relação causal entre a representação no momento passado e a representação no momento em que a lembrança é evocada. Portanto, podemos reconhecer aspectos da memória na concepção bergsoniana tanto no modelo causalista, quanto no modelo simulacionista apresentados no debate contemporâneo. A nossa pretensão é, a partir da verificação sobre quais aspectos a filosofia de Bergson se aproxima e se afasta das teorias atuais, reconhecer a quais objeções ela está exposta, bem como que vantagens tem na pesquisa contemporânea em filosofia da memória. Assim como todo estudo relacionado à mente, o trabalho em torno da memória trouxe diversas descobertas e hipóteses no último século, ou seja, o conhecimento a respeito do tema avançou significativamente desde as considerações realizadas por Bergson. Acreditamos que o resgate histórico é importante para evitar a possibilidade de que elementos inclusos em constatações filosóficas mais antigas, e que podem ser de interesse para a pesquisa atual, não sejam vistos. Dividiremos a apresentação deste trabalho em três seções: na primeira, abordaremos as teorias causalista e simulacionista da memória; na segunda, exporemos a filosofia da memória de Bergson; por fim, relacionaremos a compreensão bergsoniana acerca da memória com o debate atual para detectarmos quais aspectos foram derrotados e quais têm se mantido ao longo de todos estes anos após a publicação de Bergson. (shrink)

The distinction between lying and mere misleading is commonly tied to the distinction between saying and conversationally implicating. Many definitions of lying are based on the idea that liars say something they believe to be false, while misleaders put forward a believed-false conversational implicature. The aim of this paper is to motivate, spell out, and defend an alternative approach, on which lying and misleading differ in terms of commitment: liars, but not misleaders, commit themselves to something they believe to be (...) false. This approach entails that lying and misleading involve speech-acts of different force. While lying requires the committal speech-act of asserting, misleading involves the non-committal speech-act of suggesting. The approach leads to a broader definition of lying that can account for lies that are told while speaking non-literally or with the help of presuppositions, and it allows for a parallel definition of misleading, which so far is lacking in the debate. (shrink)

Almost all philosophers agree that a necessary condition on lying is that one says what one believes to be false. But, philosophers haven’t considered the possibility that the true requirement on lying concerns, rather, one’s degree-of-belief. Liars impose a risk on their audience. The greater the liar’s confidence that what she asserts is false, the greater the risk she’ll think she’s imposing on the dupe, and, therefore, the greater her blameworthiness. From this, I arrive at a dilemma: either the belief (...) requirement is wrong, or lying isn’t interesting. I suggest an alternative necessary condition for lying on a degree-of-belief framework. (shrink)

It is widely held that all lies are assertions: the traditional definition of lying entails that, in order to lie, speakers have to assert something they believe to be false. It is also widely held that assertion contrasts with presupposition and, in particular, that one cannot assert something by presupposing it. Together, these views imply that speakers cannot lie with presuppositions—a view that Andreas Stokke has recently explicitly defended. The aim of this paper is to argue that speakers can lie (...) with presuppositions, and to discuss some of the implications this outcome has for current research on lying, assertion and presupposition. (shrink)

A group is lying when it makes a statement that it believes to be untrue but wants the addressee(s) to believe. But how can we distinguish statements that the group believes to be untrue from honest group statements based on mistaken beliefs or confusion within the group? I will suggest a narrative constraint for honest group statements, made up of two components. Narrative coherence requires that a new group statement should not conflict with group knowledge on the matter, or beliefs (...) of relevant operative subgroups, unless a coherent rationale is given. Narrative intention looks at the process of gathering new evidence on the area of expertise of the group and requires that the group position behind the statement is formed in good faith. The narrative constraint will help to distinguish group lies from more innocent erroneous statements of group beliefs when there is an internal disagreement within the group, including in cases involving spokespersons. (shrink)

The aim of this paper is to raise two questions. The first question is: How is pessimism related to Buddhism (and vice versa)? The second question is: What relation does an immanent philosophy have to pessimism and Buddhism, if any? Using True Detective, an American television crime drama, as my point of departure, first I will outline some of the likenesses between Buddhism and pessimism. At the same time, I will show how the conduct of one of the main characters (...) in True Detective resembles the paths of Buddhism and pessimism, even though he is ethical in a strictly non-pessimistic and non-Buddhist fashion. Last, I will try to place these findings in perspective through the French philosopher Gilles Deleuze’s thoughts. Hereby, I hope to illustrate that joy, not suffering, is basic to human existence, and how human beings may overcome a spiritual pessimism. (shrink)

Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

Traditional definitions of lying require that a speaker believe that what she asserts is false. Sam Fox Krauss seeks to jettison the traditional belief requirement in favour of a necessary condition given in a credence-accuracy framework, on which the liar expects to impose the risk of increased inaccuracy on the hearer. He argues that this necessary condition importantly captures nearby cases as lies which the traditional view neglects. I argue, however, that Krauss's own account suffers from an identical drawback of (...) being unable to explain nearby cases; and even worse, that account fails to distinguish cases of telling lies from cases of telling the truth. (shrink)

Detecting introspective errors about consciousness presents challenges that are widely supposed to be difficult, if not impossible, to overcome. This is a problem for consciousness science because many central questions turn on when and to what extent we should trust subjects’ introspective reports. This has led some authors to suggest that we should abandon introspection as a source of evidence when constructing a science of consciousness. Others have concluded that central questions in consciousness science cannot be answered via empirical investigation. (...) I argue that on closer inspection, the challenges associated with detecting introspective errors can be overcome. I demonstrate how natural kind reasoning—the iterative application of inference to the best explanation to home in on and leverage regularities in nature—can allow us to detect introspective errors even in difficult cases such as judgments about mental imagery, and I conclude that worries about intractable methodological challenges in consciousness science are misguided. (shrink)

A new definition of lying is gaining traction, according to which you lie only if you say what you know to be false. Drawing inspiration from “New Evil Demon” scenarios, I present a battery of counterexamples against this “Knowledge Account” of lying. Along the way, I comment upon the methodology of conceptual analysis, the moral implications of the Knowledge Account, and its ties with knowledge-first epistemology.

This paper defends the simple view that in asserting that p, one lies iff one knows that p is false. Along the way it draws some morals about deception, knowledge, Gettier cases, belief, assertion, and the relationship between first- and higher-order norms.

Five aspects of visual change detection are reviewed. The first concerns the concept of change itself, in particular the ways it differs from the related notions of motion and difference. The second involves the various methodological approaches that have been developed to study change detection; it is shown that under a variety of conditions observers are often unable to see large changes directly in their field of view. Next, it is argued that this “change blindness” indicates that focused (...) attention is needed to detect change, and that this can help map out the nature of visual attention. The fourth aspect concerns how these results affect our understanding of visual perception—for example, the implication that a sparse, dynamic representation underlies much of our visual experience. Finally, a brief discussion is presented concerning the limits to our current understanding of change detection. (shrink)

In a recent article, Krauss (2017) raises some fundamental questions concerning (i) what the desiderata of a definition of lying are, and (ii) how definitions of lying can account for partial beliefs. This paper aims to provide an adequate answer to both questions. Regarding (i), it shows that there can be a tension between two desiderata for a definition of lying: 'descriptive accuracy' (meeting intuitions about our ordinary concept of lying), and 'moral import' (meeting intuitions about what is wrong with (...) lying), vindicating the primacy of the former desideratum. Regarding (ii), it shows that Krauss' proposed 'worse-off requirement' meets neither of these desiderata, whereas the 'comparative insincerity condition' (Marsili 2014) can meet both. The conclusion is that lies are assertions that the speaker takes to be more likely to be false than true, and their distinctive blameworthiness is a function of the extent to which they violate a sincerity norm. (shrink)

This paper is divided into two parts. In the first part, I extend the traditional definition of lying to illocutionary acts executed by means of explicit performatives, focusing on promising. This is achieved in two steps. First, I discuss how the utterance of a sentence containing an explicit performative such as “I promise that Φ ” can count as an assertion of its content Φ . Second, I develop a general account of insincerity meant to explain under which conditions a (...) given illocutionary act can be insincere, and show how this applies to promises. I conclude that a promise to Φ is insincere (and consequently a lie) only if the speaker intends not to Φ , or believes that he will not Φ , or both. In the second part, I test the proposed definition of lying by promising against the intuitions of ordinary language speakers. The results show that, unlike alternative accounts, the proposed definition makes the correct predictions in the cases tested. Furthermore, these results challenge the following necessary conditions for telling a lie with content p: that you have to assert p directly; that you have to believe that p be false; that p must be false; that you must aim to deceive the addressee into believing that p. (shrink)

What is the relationship between lying, belief, and knowledge? Prominent accounts of lying define it in terms of belief, namely telling someone something one believes to be false, often with the intent to deceive. This paper develops a novel account of lying by deriving evaluative dimensions of responsibility from the knowledge norm of assertion. Lies are best understood as special cases of vicious assertion; lying is the anti-paradigm of proper assertion. This enables an account of lying in terms of knowledge: (...) roughly, lying is telling someone something you know ain't so. (shrink)

Not every speech act can be a lie. A good definition of lying should be able to draw the right distinctions between speech acts that can be lies and speech acts that under no circumstances are lies. This paper shows that no extant account of lying is able to draw the required distinctions. It argues that a definition of lying based on the notion of ‘assertoric commitment’ can succeed where other accounts have failed. Assertoric commitment is analysed in terms of (...) two normative components: ‘accountability’ and ‘discursive responsibility’. The resulting definition of lying draws all the desired distinctions, providing an intensionally adequate analysis of the concept of lying. (shrink)

This paper considers the phenomenon of lying and the implications it has for those subjects who are capable of lying. It is argued that lying is not just intentional untruthfulness, but is intentional untruthfulness plus an insincere invocation of trust. Understood in this way, lying demands of liars a sophistication in relation to themselves, to language, and to those to whom they lie which exceeds the demands on mere truth-tellers.

Researchers have debated whether there is a relationship between a statement’s truth-value and whether it counts as a lie. One view is that a statement being objectively false is essential to whether it counts as a lie; the opposing view is that a statement’s objective truth-value is inessential to whether it counts as a lie. We report five behavioral experiments that use a novel range of behavioral measures to address this issue. In each case, we found evidence of a relationship. (...) A statement’s truth-value affects how quickly people judge whether it is a lie. When people consider the matter carefully and are told that they might need to justify their answer, they are more likely to categorize a statement as a lie when it is false than when it is true. When given options that inhibit perspective-taking, people tend to not categorize deceptively motivated statements as lies when they are true, even though they still categorize them as lies when they are false. Categorizing a speaker as “lying” leads people to strongly infer that the speaker’s statement is false. People are more likely to spontaneously categorize a statement as a lie when it is false than when it is true. We discuss four different interpretations of relevant findings to date. At present, the best supported interpretation might be that the ordinary lying concept is a prototype concept, with falsity being a centrally important element of the prototypical lie. (shrink)

Lying and fiction both involve the deliberate production of statements that fail to obey Grice’s first Maxim of Quality (“do not say what you believe to be false”). The question thus arises if we can provide a uniform analysis for fiction and lies. In this chapter I discuss the similarities, but also some fundamental differences between lying and fiction. I argue that there’s little hope for a satisfying account within a traditional truth conditional semantic framework. Rather than immediately moving to (...) a fully pragmatic analysis involving distinct speech acts of fiction-making and lying, I will first explore how far we get with the assumption that both are simply assertions, analyzed in a Stalnakerian framework, i.e. as proposals to update the common ground. (shrink)

In the philosophical debate on lying, there has generally been agreement that either the speaker believes that his statement is false, or he believes that his statement is true. This article challenges this assumption, and argues that lying is a scalar phenomenon that allows for a number of intermediate cases – the most obvious being cases of uncertainty. The first section shows that lying can involve beliefs about graded truth values (fuzzy lies) and graded beliefs (graded-belief lies). It puts forward (...) a new definition to deal with these scalar parameters, that requires that the speaker asserts what he believes more likely to be false than true. The second section shows that statements are scalar in the same way beliefs are, and accounts for a further element of scalarity, illocutionary force. (shrink)

In the philosophical literature on the definition of lying, the analysis is generally restricted to cases of flat-out belief. This chapter considers the complex phenomenon of lies involving partial beliefs – beliefs ranging from mere uncertainty to absolute certainty. The first section analyses lies uttered while holding a graded belief in the falsity of the assertion, and presents a revised insincerity condition, requiring that the liar believes the assertion to be more likely to be false than true. The second section (...) analyses assertions that express graded beliefs, exploring how mitigation and reinforcement can alter the insincerity conditions for lying. The last section considers the case of lies that attack certainty (knowledge-lies), understood as attempt to alter the hearer's graded beliefs. (shrink)

In a recent book (_Lying and insincerity_, Oxford University Press, 2018), Andreas Stokke argues that one lies iff one says something one believes to be false, thereby proposing that it becomes common ground. This paper shows that Stokke’s proposal is unable to draw the right distinctions about insincere performative utterances. The objection also has repercussions on theories of assertion, because it poses a novel challenge to any attempt to define assertion as a proposal to update the common ground.

An important moral category—dishonest speech—has been overlooked in theoretical ethics despite its importance in legal, political, and everyday social exchanges. Discussion in this area has instead been fixated on a binary debate over the contrast between lying and ‘merely misleading’. Some see lying as a distinctive wrong; others see it as morally equivalent to deliberately omitting relevant truths, falsely insinuating, or any other species of attempted verbal deception. Parties to this debate have missed the relevance to their disagreement of the (...) notion of communicative dishonesty. Communicative dishonesty need not take the form of a lie, yet its wrongness does not reduce to the wrongness of seeking to deceive. This paper therefore proposes a major shift of attention away from the lying/misleading debate and towards the topic of communicative dishonesty. Dishonesty is not a simple notion to define, however. It presupposes a difficult distinction between what is and is not expressed in a given utterance. This differs from the more familiar distinction between what is and is not said, the distinction at the heart of the lying/misleading debate. This paper uses an idea central to speech act theory to characterize dishonesty in terms of the utterer’s communicative intentions, and applies the resulting definition to a variety of contexts. (shrink)

Are slurring statements, when applied to members of the slurred group, true, false, or a little bit of both? Intuitions are mixed. And investigating more truth-value judgments is unlikely to cure the stalemate we find ourselves in. Truth-value judgments are just not up to the task. In their place, I propose we look to judgments of lying instead. This change in focus provides a new and better tool for understanding the complex semantics and pragmatics of slurs. As I argue, it (...) also suggests that slurring statements encode, conventionally implicate and presuppose the same information as statements with the slur's neutral counterpart. I then briefly apply this style of argument to the semantics and pragmatics of evaluative language more generally. (shrink)

As an empirical inquiry into the nature of meaning, semantics must rely on data. Unfortunately, the primary data to which philosophers and linguists have traditionally appealed—judgments on the truth and falsity of sentences—have long been known to vary widely between competent speakers in a number of interesting cases. The present article constitutes an experiment in how to obtain some more consistent data for the enterprise of semantics. Specifically, it argues from some widely accepted Gricean premises to the conclusion that judgments (...) on lying are semantically relevant. It then endeavors to show how, assuming the relevance of such judgments, we can use them to generate a useful, widely acceptable test for semantic content. (shrink)

Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system incorporates an optimization technique—such as Genetic Algorithms (...) (GA) or Particle Swarm Optimization (PSO)—to enhance the accuracy and response time of the detection process. The integration of optimization methods ensures that the model adapts to various driving conditions and individual differences, providing a more reliable and robust detection mechanism. (shrink)