A person’s personality is what sets them apart from everyone else. It is a comprehensible pattern of their influence, cognition, and goals that lead to their behavior. Believe it or not, a person’s eye movements are connected to this. Not only do your eyes allow you to see, but they also reveal your personality type. In the field of robotics, this is very exciting news. This knowledge of human non-verbal behavior can be transferred to socially interactive robots. Such robots would greatly exhibit human-like behavior allowing them to interact with humans in a more natural and socially acceptable way, thereby becoming more efficient and flexible.
Eye movements are a window into the mind. They are a rich source of information on who we are, how we feel, and what we do. These movements are the means to which our everyday behaviors can predict our personality traits. University of South Australia researchers conducted a study to better understand this concept. State-of-the-art machine-learning algorithms were used to demonstrate the link.
By doing so, they were able to develop a new deep learning algorithm (in partnership with the University of Stuttgart, Flinders University and the Max Planck Institute for Informatics in Germany) that can reveal your personality type (based on the Big Five personality trait model) simply by tracking eye movements.
Other studies reporting relationships between personality traits and eye movements suggest that people with similar traits tend to move their eyes in similar ways. The findings from this study are important for bridging between tightly controlled laboratory settings of these other studies and the study of natural eye movements in unconstrained real-world environments.
The Study Procedure and Details
Fifty students and staff (with a mean age of 21.9 years) of Flinders University participated in the study but data from 8 of them were excluded due to technical reasons.
They began by fitting each participant with the eye tracker apparatus. The device recorded gaze data, along with the scene through high-resolution video on a mobile phone that was carried in a cross-body bag. Participants then had to walk around campus for approximately 10 min and (using the given AUD5) purchase any items of their choice (such as a drink or confectionary) from a campus shop of their choice. Lastly, the subjects were asked to fill in well-established personality and curiosity questionnaires.
The results prove that an individual’s level of neuroticism, extraversion, agreeableness, conscientiousness, (4 of the 5 “big five” personality traits) and perceptual curiosity can be predicted from a person’s eyes.
“There’s certainly the potential for these findings to improve human-machine interactions,” Dr Tobias Loetscher says. “People are always looking for improved, personalized 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.”