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      Children’s lying behaviour in interactions with personified robots

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      Proceedings of the 30th International BCS Human Computer Interaction Conference (HCI)


      11 - 15 July 2016

      Children, Human-robot interaction, Lying behaviour, Nonverbal expressions, Verbal expressions

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          This study investigates how young children between 4 - 6 years old interact with personified robots during a lying situation. To achieve this, a temptation resistance paradigm was used, in which children were instructed to not look at a toy (behind their back) while the instructor (a robot dog, a humanoid or a human) left the room. Results revealed that regardless of the type of communication partner, children’s peeking behaviour was similar across the 3 conditions, while there was a tendency of lying more towards the robots. The majority of the children (98%) showed semantic leakage while telling a lie, and most of them (89%) lied and denied their peeking behaviour. Additionally, children generally gave more verbal responses to the robot dog and to the humanoid in comparison with the interaction with the human. Furthermore, the mean pitch of children differed between the robot conditions, i.e. the mean pitch was significantly lower in the robot dog condition in comparison with the humanoid condition. Finally, facial expression analysis showed that children generally appeared happier when they were interacting to the robot dog compared to the humanoid or human.

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          Most cited references 31

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          Socialization between toddlers and robots at an early childhood education center.

          A state-of-the-art social robot was immersed in a classroom of toddlers for >5 months. The quality of the interaction between children and robots improved steadily for 27 sessions, quickly deteriorated for 15 sessions when the robot was reprogrammed to behave in a predictable manner, and improved in the last three sessions when the robot displayed again its full behavioral repertoire. Initially, the children treated the robot very differently than the way they treated each other. By the last sessions, 5 months later, they treated the robot as a peer rather than as a toy. Results indicate that current robot technology is surprisingly close to achieving autonomous bonding and socialization with human toddlers for sustained periods of time and that it could have great potential in educational settings assisting teachers and enriching the classroom environment.
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            Detecting deception using functional magnetic resonance imaging.

            The ability to accurately detect deception is presently very limited. Detecting deception might be more accurately achieved by measuring the brain correlates of lying in an individual. In addition, a method to investigate the neurocircuitry of deception might provide a unique opportunity to test the neurocircuitry of persons in whom deception is a prominent component (i.e., conduct disorder, antisocial personality disorder, etc.). In this study, we used functional magnetic resonance imaging (fMRI) to show that specific regions were reproducibly activated when subjects deceived. Subjects participated in a mock crime stealing either a ring or a watch. While undergoing an fMRI, the subjects denied taking either object, thus telling the truth with some responses, and lying with others. A Model-Building Group (MBG, n = 30) was used to develop the analysis methods, and the methods were subsequently applied to an independent Model-Testing Group (MTG, n = 31). We were able to correctly differentiate truthful from deceptive responses, correctly identifying the object stolen, for 93% of the subjects in the MBG and 90% of the subjects in the MTG. This is the first study to use fMRI to detect deception at the individual level. Further work is required to determine how well this technology will work in different settings and populations.
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              Deception in 3-year-olds.


                Author and article information

                July 2016
                July 2016
                : 1-10
                Tilburg center for Cognition and Communication, Tilburg University

                Tilburg University, School of Humanities, PO Box 90153, 5000 LE Tilburg, The Netherlands
                © Serras et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2016 - Fusion, Bournemouth, UK

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit

                Proceedings of the 30th International BCS Human Computer Interaction Conference
                Bournemouth University, Poole, UK
                11 - 15 July 2016
                Electronic Workshops in Computing (eWiC)
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page):
                Electronic Workshops in Computing


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