Cicero is known for saying that the eyes are the window to the soul, with the potential to reveal how we feel and what we think. Recent findings appear to be supporting the statement by suggesting that your eyes may be an indicator of your type of personality, mainly by observing their movement.
The recent research involved a joint operation between several institutions including the University of South Australia, Flinders University, the Max Planck Institute for Informatics located in Germany and Flinders University.
The work involved allowing artificial intelligence technology track and monitor how the eyes belong to the 42 participants moved in a bid to demonstrate the connection between eye movement and personality. The researchers involved utilized a video-based eye-tracker that was sourced from SensorMotoric Instruments.
The researchers monitored and tracked the eye movement of all participants as they went about their normal tasks within a university campus. After doing so, they cross-examined the results with well-established questionnaires.
Findings recorded from the exercise revealed that people ’s eye movements could tell whether they are curious conscientious or sociable. What ’s more, the algorithm software utilized was able to reliably recognize four out of the five well-known personality traits including neuroticism, conscientiousness, agreeableness, and extraversion.
The results were an outstanding feat considering that all the big five personality traits consist of conscientiousness, agreeableness, extraversion, and openness.
Dr. Tobias Loetscher from the University of South Australia said that the study marked the first time for eye movement to be used in identifying personality traits. Although identifying the link between such movement and personality traits is a remarkable finding, he said that the ultimate purpose of the task involves boosting human-machine interactions in the coming years.
Tobias emphasized that the study offers new connections between past under-investigated personality traits and eye movements and provides vital insights for upcoming fields of both social robotics and social signal processing.
In fact, he added that humans are always seeking enhanced, personalized services even though most of today’s computers and robots are not socially aware, which means that they have no potential in adapting to non-verbal cues.
For Tobias Loetscher, the research offers opportunities to create both computers and robots to allow them to become extra natural as well as better when it comes to interpretation of human social signals. He also added that the results from the study provided a fundamental bridge between the research of natural eye movements and tightly regulated laboratory studies, particularly in the real world.
Tobias went on to stress his point by saying that the remarkable study has measured and tracked the visual behavior of individuals going about their normal duties. As such, the findings were drawn from more natural responses as opposed to a laboratory setting, thus making them more reliable.
To conclude his statement, the researcher from the University of South Australia acknowledged the team’s machine-learning approach that allowed them to ascertain the function of personality in giving eye movement more meaning, especially in everyday life situations. It also assisted in revealing new eye movement traits as indicators of personality traits.