(December 13, 2015) By
studying videos from high-stakes court cases, University of Michigan
researchers are building unique lie-detecting software based on real-world
data.
Their prototype considers both the speaker's words and
gestures, and unlike a polygraph, it doesn't need to touch the subject in order
to work. In experiments, it was up to 75 percent accurate in identifying who
was being deceptive (as defined by trial outcomes), compared with humans'
scores of just above 50 percent.
With the software, the researchers say they've identified
several tells. Lying individuals moved their hands more. They tried to sound
more certain. And, somewhat counterintuitively, they looked their questioners
in the eye a bit more often than those presumed to be telling the truth, among
other behaviors.
The system might one day be a helpful tool for security
agents, juries and even mental health professionals, the researchers say.
To develop the software, the team used machine-learning
techniques to train it on a set of 120 video clips from media coverage of
actual trials. They got some of their clips from the website of The Innocence
Project, a national organization that works to exonerate the wrongfully
convicted.
The "real world" aspect of the work is one of the
main ways it's different.
"In laboratory experiments, it's difficult to create a
setting that motivates people to truly lie. The stakes are not high
enough," said Rada Mihalcea, professor of computer science and engineering
who leads the project with Mihai Burzo, assistant professor of mechanical
engineering at UM-Flint. "We can offer a reward if people can lie well—pay
them to convince another person that something false is true. But in the real
world there is true motivation to deceive."