Artificial intelligence can learn about your personality by tracking eye movement

Researchers from the University of South Australia in wspoWorking with researchers from the University of Stuttgart, Flinders University and the Max Planck Institute for Informatics in Germany, using state-of-the-art machine learning algorithms, they demonstrated a link between personality and eye movements. A study on the subject was published in the „Frontiers in Human Neuroscience”.

The results of the study show that eye movements reveal whether people are sociable, conscientious or curious, and the software created by the researchers’ow can recognize it. Researchers reported that the artificial intelligence they created can recognize four personality traits from the so-called “melanoma”. Big Five (five-factor model of personality): neuroticism, extraversion, agreeableness and conscientiousness. There is another factor in the Big Five model – openness to new experiences.

During the study, researchers tracked the eye movements of 42 volunteersow whooWho undertook ordinary daily activities within the university campus. They then assessed their personality traits using personality questionnaires based on the Big Five model.

Tobias Loetscher, PhD, of the University of South Australia, said the study provided new links between previously under-researched eye movements and personality traits. He also pointed out that it provided important information on emerging areas of signal processingoin social and social robotics.

– There is a possibility that these findings will improve human-machine interactions. People are always looking for better, personalized services. However, today’s robots and computers are not socially aware, so they cannot adapt to signaloin non-verbal – explained Loetscher.

The scientist added that the research offers opportunities for the development of the robotoin and computeroin whichore can become more natural and better interpret human signals. The findings represent a roalso an important bridge between tightly controlled laboratory tests and the study of natural movementsoin eyeballs in real-world environments.

– The study tracked and measured the behavior of osob performing everyday tasks, providing more natural responses than if they were performed in a laboratory. With our machine learning approach, we are not only confirming the role of personality in explaining eye movement in everyday life, but also discovering new features of movementow eyeballs as a predictor of personality traits – admitted Loetscher.