Incredible AI can predict your personality just by studying the motion and size of your pupils
What do your eye movements say about you? Incredible AI
can predict your personality just by studying the motion and size of your
pupils
Curious people look around more and open-minded people
stare at images
Scientists say this finding could help robots better
understand humans
Questionnaire broke down personality into 'Big Five'
traits used in psychology
By PHOEBE WESTON FOR MAILONLINE 08:51 EDT, 3 May 2018
You eyes may be able to reveal more about you than you
realise.
Scientists have created a 'mind-reading' AI that can
predict your personality from looking at pupil movements and blinking.
Curious people tend to look around more and open-minded
people stare at abstract images for longer periods of time, researchers revealed.
Scientists, led by Tobias Loetscher from the University
of South Australia, used machine learning to understand how eye movements and
personality are related.
Forty-two students wore eye-tracking smart glasses while
walking around campus, writes New Scientist.
The students also filled out questionnaires that rated
their personalities.
This questionnaire broke down personality into the 'Big
Five' traits used widely in psychology; extraversion, neuroticism,
conscientiousness, agreeableness, and openness to experience.
'Personality traits characterise an individual's patterns
of behaviour, thinking, and feeling', researchers wrote in their paper
published in Frontiers in Human Neuroscience.
'Studies reporting relationships between personality
traits and eye movements suggest that people with similar traits tend to move
their eyes in similar ways.'
Researchers found that people who were neurotic usually
blinked faster while people who were open to new experiences moved their eyes
more from side-to-side.
People who had high levels of conscientiousness had
greater fluctuations in their pupil size.
Optimists spent less time looking at negative emotional
stimuli (such as image of skin cancer) than people who were pessimistic.
Researchers led by Tobias Loetscher from the University
of South Australia used machine learning to understand how eye movements and
personality are related.
Forty-two students wore eye-tracking smart glasses while
walking around campus and from this experiment they have created an AI that can
predict someone's personality.
- Curious people tend to look around more.
- Open-minded people stare at abstract images for longer
periods of time.
- People who are neurotic usually blink faster.
- People who are open to new experiences moved their eyes
more from side-to-side.
- People who have high levels of conscientiousness have
greater fluctuations in their pupil size.
- Optimists spend less time looking at negative emotional
stimuli (such as image of skin cancer) than people who were pessimistic.
This technology could be put in smartphones that
understand and predict our behaviour, potentially offering personalised support.
They could also be used by robot companions for older
people, or in self-driving cars and interactive video games.
'Besides allowing us to perceive our surroundings, eye
movements are also a window into our mind and a rich source of information on
who we are, how we feel, and what we do', researchers wrote.
'The proposed machine learning approach was particularly
successful in predicting levels of agreeableness, conscientiousness,
extraversion, and perceptual curiosity'.
Scientists found the machine is currently between seven
and 15 per cent better than random chance at predicting these traits.
However, it is no better than random chance at predicting
openness.
Researcher do not know why there are these links but say
that it will help them to teach robots to be more socially aware.
It could be put in smartphones that understand and
predict our behaviour, potentially offering personalised support.
They could also be used by robot companions for older
people, or in self-driving cars and interactive video games.
Researchers warn that the technology would have to be
regulated so it was not misused by marketers.
'Improving automatic recognition and interpretation of
human social signals is an important endeavor, enabling innovative design of
human–computer systems capable of sensing spontaneous natural user behavior to
facilitate efficient interaction and personalization', researchers wrote.
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