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AI can fool us humans, but not at the psycho-physiological level: a hyperscanning and physiological synchrony study

Dehais, Frédéric and Vergotte, Grégoire and Drougard, Nicolas and Ferraro, Giuseppe and Somon, Bertille and Ponzoni Carvalho Chanel, Caroline and Roy, Raphaëlle N. AI can fool us humans, but not at the psycho-physiological level: a hyperscanning and physiological synchrony study. (2021) In: IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2021), 17 October 2021 - 20 October 2021 (Virtual event, Australia).

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This study aims at investigating the neural and physiological correlates of human-human and human-AI interactions under ecological settings. We designed a scenario in which a ground controller had to guide his/her pilot to reach a location. We also implemented a Controller-Bot and a Pilot-Bot using AI techniques to behave like real human operators. The cooperation between controllers and pilots were either genuine (‘Coop scenarios’ – four missions), explicitly notified as pilot-Bot and controller-Bot interactions (‘No coop scenarios’ – two missions), or with no notification that they were actually collaborating with their AI counterparts (‘fake coop scenarios’ – two missions). Sixteen participants (8 dyads) equipped with EEG and ECG took part in this experiment. Our findings disclosed that Human-Human dyads exhibited similar performance to Human-Bots dyads whether the human participants were aware that they were playing with a bot or not. Our participants declared that they did not realize they were playing with an AI in the fake cooperation condition. These findings indicate that 1) humans can be fooled by AI, and that 2) humans can behave in a natural way with AI. Interestingly enough, our analyses revealed that the cardiac activity of controllers and pilots was more synchronized when they were collaborating together than when they were playing with AI (being aware or not). Similarly, EEG analyses disclosed a higher cerebral efficiency and connectivity between the two brains when teammates were interacting together than when cooperating with AI.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-03384963
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Other partners > Drexel University (USA)
Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
French research institutions > Artificial and Natural Intelligence Toulouse Institute - ANITI (FRANCE)
Laboratory name:
Agence Innovation Défense - ANITI ANR-19-PI3A-0004
Deposited On:27 Aug 2021 12:35

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