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This software uses data from court cases to accurately detect lies

Lie detectors have been around for almost a century, but none of them have even come close to detecting lies as well as a human can, which isn’t saying much, because most humans aren’t that accurate either. However, a group of researchers from the University of Michigan has spent hours reviewing videos from high-stakes court cases to develop a lie-detecting software database that’s significantly more accurate than humans. By analyzing someone’s gestures and words, the software can determine whether or not the person is lying with 75% accuracy, compared to the 50% accuracy of humans. 

A group of researchers from the University of Michigan may have found a better way to detect whether you’re lying – and it’s not the polygraph test. Using videos from high-stakes court cases, the researchers have built a lie-detecting software database that uses a person’s words and gestures to detect behavioral patterns that may be out of the norm. While the software is still being tested, it was 75 percent accurate in identifying a deceptive subject during testing. Humans were only 50 percent accurate in guessing. The database for the software took typical “lying behavior” – individuals who moved their hands more, tried to sound more confident and looked their questioners in the eye were more likely to be lying – and was taught to recognize these patterns in humans. Using machine-learning techniques, the team trained the software on a set of 120 video clips from actual trials. “People are poor lie detectors,” said Rada Mihalcea, professor of computer science and engineering in a news release. “This isn’t the kind of task we’re naturally good at. There are clues that humans give naturally when they are being deceptive, but we’re not paying close enough attention to pick them up. We’re not counting how many times a person says ‘I’ or looks up. We’re focusing on a higher level of communication.”

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Written by Chastity Mansfield

I'm a writer, an amateur designer, and a collector of trinkets that nobody else wants. You can find me on Noozeez, and Twitter.

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