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date: 15 December 2019

Abstract and Keywords

This chapter is from the forthcoming The Oxford Handbook of Affective Computing edited by Rafael Calvo, Sidney K. D'Mello, Jonathan Gratch, and Arvid Kappas. In response to national security needs and the limitations of human deception detection—along with advances in sensor and computing technology—research into automated deception detection has increased in recent years. In order to interpret when behavioral and physiological cues reveal deception, these technologies rely on psychological and communication theories of deception. Despite the need, the technology for detecting deception that is available to law enforcement or border guards is very limited. Deception theories suggest that liars are likely to exhibit both strategic and nonstrategic behavior. In order to develop algorithms and technology to detect and classify deception, such behaviors and physiological cues must be measured remotely. These measurements can be categorized by their theoretical causes when a person is lying; they include arousal, negative affect, cognitive effort, behavioral control, memory processes, and strategic activity. One major challenge to deception detection is accounting for the variability introduced by human interviewers. Future research should focus more on behavior over the entire interaction, thus fusing multiple behavioral indicators.

Keywords: deception, nonverbal behavior, physiological cues, automated deception detection, strategic and nonstrategic behavior, theoretical

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