Is it really possible to read a lie in someone’s face? A brief history of the science of human lie detection.
Tim Roth’s portrayal of Dr. Cal Lightman in the hit Fox series, “Lie to Me,” glorified and popularized an experimental new method of investigation: the art of human lie detecting by searching for subtle indicators of emotion in people’s faces.
Although an inexact science, the techniques have evolved and have potential applications in law enforcement, health care, and even marketing.
“The World’s Most Famous Face Reader“
The real-life (although very loose) inspiration for Cal Lightman, psychologist Paul Ekman, pioneered the science of reading and cataloging micro-expressions—lightning-quick flashes of contempt, fear, or anger in people’s faces—and has recently collaborated in developing software apps based on what he’s learned about the human face.
He’s helped the CIA, the FBI, the U.S. military, and TSA develop systems for interpreting subtle facial expressions and body language, for use in airport screening and nonviolent interrogation of enemy combatants (among other potential applications).
Facial emotion measurement techniques also have practical uses beyond security and law enforcement. Ekman has helped animators at Pixar draw more expressive cartoon characters, Apple, and Microsoft are finding ways to use facial analysis, and even the Dalai Lama has consulted with Ekman—the two co-authored a book called Emotional Awareness: Overcoming the Obstacles to Psychological Balance and Compassion.
How It’s Done
According to Ekman’s research, there are seven universal emotions that register clearly on the face: anger, contempt, fear, sadness, surprise, happiness, and disgust. But the 43 muscles of the face arrange themselves into thousands of combinations—all manner of tics and furrowed brows—which Ekman has catalogued into a Facial Action Coding System (FACS).
Those tiny expressions may only register for a fraction of a second. But with practice, people can learn to spot these quick-fire facial movements and the emotions that correspond to them. (You can take a basic online course in recognizing micro-expressions at Ekman’s website.)
Although there are automated systems for analyzing facial expressions, Ekman contends that specially trained human observers do the job better.
Unlimited Potential
Still, there’s significant interest in automated face-reading technology in various industries. A company called Machine Perception Technologies (MPT) has developed methods for automating facial measurement, with applications in the security and marketing fields. Affectiva, a firm seeded from MIT Media Lab, focuses on applications in market research—helping companies, marketers, and advertisers “discover the true emotional insight behind consumer response,” in order to learn which ads evoke emotional reactions.
What lies ahead for the fascinating (if inexact) science of facial expression measurement? If emotion is universal, then our faces really are windows into our souls and motives, and perhaps even our futures. What if we could read Hitler’s genocidal intent on his brow? A bomber’s plan as he boards the subway? Or a teen girl’s determination to commit suicide?
Or if, as Ekman claims, the expressions on our faces can actually bring about the corresponding feeling, perhaps Ekman’s art can teach us to train our emotions by using our faces. And that could lead us to happier lives.
“Let a smile be your umbrella on a rainy, rainy day.”
-song lyrics by Irving Kahal and Francis Wheeler
Michelle Rebecca is a blogger and freelance writer. She’s written about almost every topic under the sun, and loves constantly learning about new subjects and industries while she’s writing. In her spare time she enjoys spending time outdoors with her dogs. Follow her on Twitter and Google+.