Computer identifies liars at a much higher rate than experienced interrogators

University at Buffalo computer scientists are exploring how machines can read the visual cues that give away deceit. Results so far are promising: In a study of 40 videotaped conversations, an automated system that analyzed eye movements correctly identified whether interview subjects were lying or telling the truth 82.5 percent of the time. Ifeoma Nwogu, a research assistant professor at UB's Center for Unified Biometrics and Sensors (CUBS) who helped develop the system, stated that it was a better accuracy rate than what expert human interrogators typically achieve in lie-detection judgment experiments. In published results, even experienced interrogators average closer to 65 percent, Nwogu said. They suggest that computers may be able to learn enough about a person's behavior in a short time to assist with a task that challenges even experienced interrogators. The videos used in the study showed people with various skin colors, head poses, lighting and obstructions such as glasses. However, this does not mean machines are ready to replace human questioners; they are merely advanced tools to assist in human lie detection.