
In
the ever-expanding contest between artificial intelligence and the
ordinary human mind, you can chalk up another one for the computer.
Scientists
have developed a computer system with sophisticated pattern recognition
abilities that performed much better than humans in differentiating
between people experiencing genuine pain and people who were just faking
it.
In a study published in the journal
Current Biology this week, human subjects did no better than chance —
about 50% — in correctly judging if a person was feigning pain after
seeing videos in which some people were and some were not.
The
computer was right 85% of the time. Why? The researchers say its
pattern recognition abilities successfully spotted distinctive aspects
of facial expressions, particularly involving mouth movements, that
people generally missed.
"We all know that
computers are good at logic processes and they've long out-performed
humans on things like playing chess," said Marian Bartlett of the
Institute for Neural Computation at the University of California-San
Diego, one of the researchers.
"But in
perceptual processes, computers lag far behind humans and have a lot of
trouble with perceptual processes that humans tend to find easy,
including speech recognition and visual recognition. Here's an example
of a perceptual process that the computer is able to do better than
human observers," Bartlett said in a telephone interview.
For the experiment, 25 volunteers each recorded two videos.
In
the first, each of the volunteers immersed an arm in lukewarm water for
a minute and were told to try to fool an expert into thinking they were
in pain. In the second, the volunteers immersed an arm in a bucket of
frigid ice water for a minute, a genuinely painful experience, and were
given no instructions on what to do with their facial expressions.
The researchers asked 170 other volunteers to assess which people were in real discomfort and which were faking it.
After
they registered a 50% accuracy rate, which is no better than a coin
flip, the researchers gave the volunteers training in recognizing when
someone was faking pain. Even after this, the volunteers managed an
accuracy rate of only 55%.
The computer's
vision system included a video camera that took images of a person's
facial expressions and decoded them. The computer had been programmed to
recognize that one kind of facial movement combinations suggested true
pain and another kind suggested faked pain.
"It's looking at what 20 facial muscles are doing in every frame of video," Bartlett added.
So
why are people so lousy at spotting a faker? The human face transmits
an abundance of information including expressions of emotion and pain.
But people also are adept at simulating emotions, some are so good they
routinely can deceive others.
The computer
system proved far better than people at spotting subtle differences
between involuntary and voluntary facial movements that underpin
sincerity, the researchers said.
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