Results 1 to 10 of about 5,077 (161)

Ethics and Fairness Considerations in AI-Based Deception Detection Technologies for Mental Health Applications: Focus Group Study [PDF]

JMIR AI
BackgroundArtificial intelligence (AI) technologies are increasingly being integrated into mental health settings to support tasks such as clinical documentation and decision-making. In parallel, AI-enabled deception detection, which leverages multimodal
Sayde Leya King, Serena Bhaskar, Julia Woodward, Tempestt Neal   +3 more
doaj   +2 more sources

You can’t kid a kidder: Association between production and detection of deception in an interactive deception task

Frontiers in Human Neuroscience, 2012
Both the ability to deceive others, and the ability to detect deception, have long been proposed to confer an evolutionary advantage. Deception detection has been studied extensively, and the finding that typical individuals fare little better than ...
Gordon R.T. Wright, Christopher J Berry, Geoffrey eBird   +2 more
doaj   +3 more sources

A deception detection model by using integrated LLM with emotion features [PDF]

Scientific Reports
Traditional lie detection relies on the experience of human interrogators, making it susceptible to subjective factors and leading to misjudgments. To solve this problem, we propose an emotion-enhanced deception detection model, Lie Detection using ...
Chucheng Zhou, Yingqian Zhang, Chengcong Lin, Shuang Zhou   +3 more
doaj   +2 more sources

Emotional intelligence and mismatching expressive and verbal messages: a contribution to detection of deception. [PDF]

PLoS ONE, 2014
Processing facial emotion, especially mismatches between facial and verbal messages, is believed to be important in the detection of deception. For example, emotional leakage may accompany lying. Individuals with superior emotion perception abilities may
Jerzy Wojciechowski, Maciej Stolarski, Gerald Matthews   +2 more
doaj   +2 more sources

Multimodal machine learning for deception detection using behavioral and physiological data [PDF]

Scientific Reports
Deception detection is crucial in domains like national security, privacy, judiciary, and courtroom trials. Differentiating truth from lies is inherently challenging due to many complex, diversified behavioural, physiological and cognitive aspects ...
Gargi Joshi, Vaibhav Tasgaonkar, Aditya Deshpande, Aditya Desai, Bhavya Shah, Akshay Kushawaha, Aadith Sukumar, Kermi Kotecha, Saumit Kunder, Yoginii Waykole, Harsh Maheshwari, Abhijit Das, Shubhashi Gupta, Akanksha Subudhi, Priyanka Jain, N. K. Jain, Rahee Walambe, Ketan Kotecha   +17 more
doaj   +2 more sources

LegalEye: Multimodal Court Deception Detection Across Multiple Languages [PDF]

Behavioral Sciences
This study introduces LegalEye, a multimodal machine-learning model developed to detect deception in courtroom settings across three languages: English, Spanish, and Tagalog.
Rommel Isaac A. Baldivas, Nivedha Sreenivasan, So Young Kang, Alexandra My-Linh Miller, Megan Chacko, Shreya Krishnan, Carmen Ayala, Esperanza Ayala, Dohyeong Kim   +8 more
doaj   +2 more sources

Contextual considerations for deception production and detection in forensic interviews

Frontiers in Psychology, 2023
Most deception scholars agree that deception production and deception detection effects often display mixed results across settings. For example, some liars use more emotion than truth-tellers when discussing fake opinions on abortion, but not when ...
David M. Markowitz, Jeffrey T. Hancock, Michael T. Woodworth, Maxwell Ely   +3 more
doaj   +1 more source

HOW PEOPLE [TRY TO] DETECT LIES IN EVERYDAY LIFE [PDF]

Trames, 2021
Laboratory-based deception-detection experiments often fail to capture the features of everyday life lie detection among ordinary citizens. In this study, we examined how people [try to] detect deception in real life.
Nuria Sánchez, Jaume Masip, Carmen Herrero   +2 more
doaj   +1 more source

Survey of software anomaly detection based on deception

网络与信息安全学报, 2022
Advanced persistent threats (APT) will use vulnerabilities to automatically load attack code and hide attack behavior, and exploits code reuse to bypass the non-executable stack ＆amp; heap protection, which is an essential threat to network security ...
Jianming FU, Chang LIU, Mengfei XIE, Chenke LUO   +3 more
doaj   +3 more sources

Computational Measures of Deceptive Language: Prospects and Issues

Frontiers in Communication, 2022
In this article, we wish to foster a dialogue between theory-based and classification-oriented stylometric approaches regarding deception detection. To do so, we review how cue-based and model-based stylometric systems are used to detect deceit. Baseline
Frédéric Tomas, Frédéric Tomas, Olivier Dodier, Samuel Demarchi   +3 more
doaj   +1 more source