Computers catch fake pain better than people

Scientists have found that a computer system can spot real or faked expressions of pain more accurately than people.
Researchers at the University of California, San Diego and the University of Toronto found that humans could not discriminate real from faked expressions of pain better than random chance - and, even after training, only improved accuracy to a modest 55 per cent.
In contrast, the computer system attained an 85 per cent accuracy.
"The computer system managed to detect distinctive dynamic features of facial expressions that people missed," said Marian Bartlett, research professor at UC 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," Bartlett said.
"Humans can simulate facial expressions and fake emotions well enough to deceive most observers. The computer's pattern-recognition abilities prove better at telling whether pain is real or faked," said senior author Kang Lee, professor at the Dr Eric Jackman Institute of Child Study at the University of Toronto.

"In highly social species such as humans faces have evolved to convey rich information, including expressions of emotion and pain," said Lee.
"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," Lee said.
The single most predictive feature of falsified expressions, the study found, is the mouth, and how and when it opens. Fakers' mouths open with less variation and too regularly.
In addition to detecting pain malingering, 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 minimise, 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," she added.
The study is published in the journal Current Biology.