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IEEE AccessArtificial intelligence-enabled deception detection is an emerging tool for identifying dishonest behavior in a wide range of applications, from security and forensics to politics and lower-risk everyday interactions, addressing the pressing need for ...
Sayde L. King, Tempestt Neal
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Telaah Metode-metode Pendeteksi Kebohongan
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2013 Abstrak Pendeteksi kebohongan adalah aplikasi yang menerapkan berbagai cabang ilmu pengetahuan(psikologi,kedokteran,biologi,fisika,komputer,dan lain lain).
I Gede Aris Gunadi, Agus Harjoko
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Domain-Independent Deception: Definition, Taxonomy and the Linguistic Cues Debate [PDF]
arXiv, 2022 Internet-based economies and societies are drowning in deceptive attacks. These attacks take many forms, such as fake news, phishing, and job scams, which we call "domains of deception." Machine-learning and natural-language-processing researchers have been attempting to ameliorate this precarious situation by designing domain-specific detectors.
arxiv
Unobtrusive Deception Detection [PDF]
, 2015 In response to national security needs and human deception detection limitations paired with advances in sensor and computing technology research into automated deception detection has increased in recent years. These technologies rely on psychological and communication theories of deception to interpret when behavioral and physiological cues reveal ...
Rafael Calvo +7 more
openaire +2 more sources
Exploring Machine Learning and Transformer-based Approaches for Deceptive Text Classification: A Comparative Analysis [PDF]
arXiv, 2023 Deceptive text classification is a critical task in natural language processing that aims to identify deceptive o fraudulent content. This study presents a comparative analysis of machine learning and transformer-based approaches for deceptive text classification.
arxiv
Acta Psychologica, 2022 People deceive for different reasons, from avoiding interpersonal conflicts to preserving, protecting, and nurturing interpersonal relationships, and to obtaining social status and power.
Andreea Turi +2 more
doaj
AI Deception: A Survey of Examples, Risks, and Potential Solutions [PDF]
arXiv, 2023 This paper argues that a range of current AI systems have learned how to deceive humans. We define deception as the systematic inducement of false beliefs in the pursuit of some outcome other than the truth. We first survey empirical examples of AI deception, discussing both special-use AI systems (including Meta's CICERO) built for specific ...
arxiv
Dataset Bias in Deception Detection
2022 26th International Conference on Pattern Recognition (ICPR), 2022 With the advances in Machine Learning, lie detection technology gained significant attention. In recent years, several multi-modal techniques achieved as high as 99% accuracy results using the Real-life Trial dataset with only 121 data points. This led to considerable media hype and research interest in lie detection with machine learning.
Mambreyan, Ara +2 more
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Advanced Functional Materials, EarlyView.By using (meso)porous N‐doped carbon nanospheres with tailored intraparticle porosity and constant particle size as conductive carbon in PVMPT‐based organic battery electrodes, the complete volume of the carbon is accessible for the immobilization of PVMPT, resulting in high accessible specific capacities while maintaining a good rate capability and ...
Niklas Ortlieb +6 more
wiley +1 more source
Frontiers in Neuroscience, 2021 Deception is a complex and cognitively draining dyadic process that simultaneously involves cognitive and emotional processes, both of which demand/capture attentional resources.
Jing Liang +4 more
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