Posted in | Medical Robotics

AI Used to Track Person’s Eye Movement & Reveal Personality

‘The eyes are the window to the soul’ is a common adage, meaning that the eyes reveal what a person thinks and how they feel.

Image credit: University of South Australia

A recent research shows that one’s eyes may also be an indicator of one’s personality type, simply by the way they move.

The study, developed by the University of South Australia in collaboration with the University of Stuttgart, Flinders University and the Max Planck Institute for Informatics in Germany, uses advanced machine-learning algorithms to show a connection between personality and eye movements.

Findings reveal that people’s eye movements expose whether they are conscientious, sociable, or curious, with the algorithm software reliably identifying four of the Big Five personality traits: neuroticism, agreeableness, extroversion, and conscientiousness.

Scientists monitored the eye movements of 42 participants as they went about their daily tasks around a university campus, and then evaluated their personality traits using proven questionnaires.

UniSA’s Dr Tobias Loetscher says the research offers new links between formerly under-investigated eye movements and personality traits and delivers vital insights for evolving fields of social robotics and social signal processing.

“There’s certainly the potential for these findings to improve human-machine interactions,” Dr Loetscher says.

“People are always looking for improved, personalised services. However, today’s robots and computers are not socially aware, so they cannot adapt to non-verbal cues.

“This research provides opportunities to develop robots and computers so that they can become more natural, and better at interpreting human social signals.”

Dr Loetscher says the findings also offer a crucial bridge between securely controlled laboratory studies and the study of natural eye movements in real-world settings.

“This research has tracked and measured the visual behaviour of people going about their everyday tasks, providing more natural responses than if they were in a lab.

“And thanks to our machine-learning approach, we not only validate the role of personality in explaining eye movement in everyday life, but also reveal new eye movement characteristics as predictors of personality traits.”

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