Sociable, conscientious or curious? It’s all in the eyes.

Sociable, conscientious or curious? It’s all in the eyes.

Photo by Quinten de Graaf on Unsplash

From the Myers-Briggs Type Indicator to astrology, we have long embraced tools that help predict our personality traits. Now, artificial intelligence can predict your personality by tracking your eyes.

New research reveals that, in addition to 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 – simply by the way they move.

Developed by the University of South Australia in partnership with the University of Stuttgart, Flinders University and the Max Planck Institute for Informatics in Germany, the research uses state-of-the-art machine-learning algorithms to demonstrate a link between personality and eye movements.

Researchers tracked the eye movements of 42 participants while they ran an errand on a university campus and subsequently assessed their personality traits using well-established questionnaires.

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

UniSA’s Dr Tobias Loetscher says the study provides new links between previously under-investigated eye movements and personality traits and delivers important insights for emerging fields of social signal processing and social robotics.

“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 provide an important bridge between tightly controlled laboratory studies and the study of natural eye movements in real-world environments.

“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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