The use of artificial intelligence in interrogation: lies and truth

Yi-Chang Wu, Yao-Cheng Liu, Ru-Yi Huang


Following the development of artificial intelligence technology, a new trend has emerged in which this technology is increasingly used in case investigations. In this study, we developed a lie detection system that can instantly determine whether an interrogee is lying depending on their emotional responses to specific questions. Investigators then use these data, in addition to their personal experiences and case information, to adjust their interrogation strategies and techniques, thereby leading the interrogee to confess and accelerating the investigation process. Our system collects data using OpenFace and performs deep learning using gcForest. Deep learning training was performed using a real-life trial dataset, the Miami University Deception Detection Database, and a bag-of-lies dataset, and their corresponding trained systems achieved a detection accuracy of 95.11%, 90.83%, and 88.19%, respectively.


Artificial intelligence; Deception detection; gcForest; Micro expression; Real-time recognition

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IAES International Journal of Robotics and Automation (IJRA)
ISSN 2089-4856, e-ISSN 2722-2586
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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