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Using a Gaze-Cueing Paradigm to Examine Social Cognitive Mechanisms of Individuals with Autism Observing Robot and Human Faces

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Social Robotics (ICSR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8755))

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Abstract

This paper reports a study in which we investigated whether individuals with autism spectrum disorder (ASD) are more likely to follow gaze of a robot than of a human. By gaze following, we refer to one of the most fundamental mechanisms of social cognition, i.e., orienting attention to where others look. Individuals with ASD sometimes display reduced ability to follow gaze [1] or read out intentions from gaze direction [2]. However, as they are in general well responding to robots [3], we reasoned that they might be more likely to follow gaze of robots, relative to humans. We used a version of a gaze cueing paradigm [4, 5] and recruited 18 participants diagnosed with ASD. Participants were observing a human or a robot face and their task was to discriminate a target presented either at the side validly cued by the gaze of the human or robot; or at the opposite side. We observed typical validity effects: faster reaction times (RTs) to validly cued targets, relative to invalidly cued targets. However, and most importantly, the validity effect was larger and significant for the robot faces, as compared to the human faces, where the validity effect did not reach significance. This shows that individuals with ASD are more likely to follow gaze of robots, relative to humans, suggesting that the success of robots in involving individuals with ASD in interactions might be due to a very fundamental mechanism of social cognition. Our present results can also provide avenues for future training programs for individuals with ASD.

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Wiese, E., Müller, H.J., Wykowska, A. (2014). Using a Gaze-Cueing Paradigm to Examine Social Cognitive Mechanisms of Individuals with Autism Observing Robot and Human Faces. In: Beetz, M., Johnston, B., Williams, MA. (eds) Social Robotics. ICSR 2014. Lecture Notes in Computer Science(), vol 8755. Springer, Cham. https://doi.org/10.1007/978-3-319-11973-1_38

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  • DOI: https://doi.org/10.1007/978-3-319-11973-1_38

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11972-4

  • Online ISBN: 978-3-319-11973-1

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