Human vs Robot Lie Detector: Better Working as a Team?

نویسندگان

چکیده

Human interaction often entails lies. Understanding when a partner is being deceitful an important social skill, that also robots will need, to properly navigate exchanges. In this work, we investigate how good are human observers at detecting false claims and which features they base their judgment on. Moreover, compare performance with of algorithm for lie detection developed the robot iCub based uniquely on pupillometry. We ran online survey asking participants classify as truthful or deceptive 20 videos individuals describing complex drawings iCub, either correctly untruly. They had rate confidence provide written motivation each classification. Responders achieved average accuracy 53.9% higher score lies (55.4%) respect true statements (52.8%). Also, performed better more confidently failed than ones detected. Interestingly, listed wide range behavioral means decide whether speaker was lying, while robot’s driven by pupil size only. This suggests avenue improving could be joint effort between humans robots, where sensitivity subtle cues complement quantitative assessment physiological signals feasible robot. Finally, reported motivations, speculate give hints field should evolve in future, aiming portability real-world interactions.

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ژورنال

عنوان ژورنال: Lecture Notes in Computer Science

سال: 2021

ISSN: ['1611-3349', '0302-9743']

DOI: https://doi.org/10.1007/978-3-030-90525-5_14