Computer System Can Spot Fakers Better Than People
“The computer system managed to detect distinctive dynamic features of facial expressions that people missed,” said Marian Bartlett, Ph.D., a research professor at the University of California San Diego’s Institute for Neural Computation and lead author of the study.
“Human observers just aren’t very good at telling real from faked expressions of pain.”
That’s because “humans can simulate facial expressions and fake emotions well enough to deceive most observers,” said Kang Lee, Ph.D., a professor at the University of Toronto and senior author of the study. “The computer’s pattern-recognition abilities prove better at telling whether pain is real or faked.”
The research team found that humans could not discriminate real from faked expressions of pain better than random chance. Even after some training, accuracy was only improved to 55 percent. That pales in comparison to the computer’s 85 percent accuracy.
“In highly social species such as humans, faces have evolved to convey rich information, including expressions of emotion and pain,” Lee said.
“And, because of the way our brains are built, people can simulate emotions they’re not actually experiencing so successfully that they fool other people. The computer is much better at spotting the subtle differences between involuntary and voluntary facial movements.”
The single most predictive feature of false expressions is the mouth, and how and when it opens, according to the study’s findings. Fakers’ mouths open with less variation and too regularly.
“Further investigations will explore whether over-regularity is a general feature of fake expressions,” the researchers said in the study, which was published in Current Biology.
“In addition to detecting pain — real and false — the computer-vision system might be used to detect other real-world deceptive actions in the realms of homeland security, psychopathology, job screening, medicine and law,” said Bartlett.
“As with causes of pain, these scenarios also generate strong emotions, along with attempts to minimize, mask, and fake such emotions, which may involve ‘dual control’ of the face,” she said.
“In addition, our computer-vision system can be applied to detect states in which the human face may provide important clues as to health, physiology, emotion, or thought, such as drivers’ expressions of sleepiness, students’ expressions of attention and comprehension of lectures, or responses to treatment of affective disorders.”
Source: University of Toronto
Wood, J. (2018). Computer System Can Spot Fakers Better Than People. Psych Central. Retrieved on September 30, 2020, from https://psychcentral.com/news/2014/03/22/computer-system-can-spot-fakers-better-than-people/67473.html