Date:31/07/18
Their 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.
Researchers tracked the eye movements of 42 participants as they undertook everyday tasks around a university campus, and subsequently assessed their personality traits using well-established questionnaires.
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. People are always looking for improved, personalised services," said Tobias Loetscher, of University of South Australia.
"However, today's robots and computers are not socially aware, so they cannot adapt to non-verbal cues," said Loetscher.
"This research provides opportunities to develop robots and computers so that they can become more natural, and better at interpreting human social signals," he said.
The findings also provide an important bridge between tightly controlled laboratory studies and the study of natural eye movements in real-world environments, researchers said.
Artificial intelligence system can identify your personality from eye movements
Scientists have developed a new artificial intelligence system that can track a person's eye movements to identify their personality type. Researchers, including those from the University of Stuttgart in Germany and Flinders University in Australia used state-of-the-art machine-learning algorithms to demonstrate a link between personality and eye movements.Their 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.
Researchers tracked the eye movements of 42 participants as they undertook everyday tasks around a university campus, and subsequently assessed their personality traits using well-established questionnaires.
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. People are always looking for improved, personalised services," said Tobias Loetscher, of University of South Australia.
"However, today's robots and computers are not socially aware, so they cannot adapt to non-verbal cues," said Loetscher.
"This research provides opportunities to develop robots and computers so that they can become more natural, and better at interpreting human social signals," he said.
The findings also provide an important bridge between tightly controlled laboratory studies and the study of natural eye movements in real-world environments, researchers said.
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