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Look at Me Now: Investigating Delayed Disengagement for Ambiguous Human-Robot Stimuli

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Social Robotics (ICSR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9979))

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Abstract

Human-like appearance has been shown to positively affect perception of and attitudes towards robotic agents. In particular, the more human-like robots look, the more participants are willing to ascribe human-like states to them (i.e., having a mind, emotions, agency). The positive effect of human-likeness on agent ratings, however, does not translate to better performance in human-robot interaction (HRI). Performance first increases as human-likeness increases, then drops dramatically as soon as human-likeness reaches around 70 % to finally reach its maximum at 100 % humanness. The goal of the current paper is to investigate whether attentional mechanisms, in particular delayed disengagement, are responsible for the drop in performance for very human-like, but not perfectly human agents. The idea is that robots with a high degree of human-likeness capture attention and thus make it harder to orient attention away from them towards task-relevant stimuli in the periphery resulting in bad performance. To investigate this question, faces of differing degrees of human-likeness (0 %, 30 %, 70 %, 100 %, non-social control) are presented to participants in an eye-tracking experiment and the time it takes participants to orient towards a peripheral stimulus is measured. Results show significant delayed disengagement for all stimuli, but no stronger delayed disengagement for very human-like agents, making delayed disengagement an unlikely source for the negative effect of human-like appearance on performance in HRI.

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Notes

  1. 1.

    A pilot version of this study was conducted with the same agent across the spectrum with the same results.

  2. 2.

    Post-hoc t-tests of the differences in the SOAs at the agent-level revealed a significant difference between SOA 50 and SOA 200 only in the humanoid (t(35) = 2.577, p = .014, η² = .209) condition, but not in any of the other conditions.

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Authors and Affiliations

  1. Department of Psychology, George Mason University, Fairfax, Virginia, 22031, USA

    Melissa A. Smith & Eva Wiese

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  1. Melissa A. Smith
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  2. Eva Wiese
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Correspondence to Melissa A. Smith .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, The University of Kansas, Lawrence, Indiana, USA

    Arvin Agah

  2. Department of Mechanical Engineering, Qatar University, Doha, Qatar

    John-John Cabibihan

  3. School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA

    Ayanna M. Howard

  4. Department of Systems Engineering and Automation, University Carlos III de Madrid, madrid, Spain

    Miguel A. Salichs

  5. Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, Tennessee, USA

    Hongsheng He

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Smith, M.A., Wiese, E. (2016). Look at Me Now: Investigating Delayed Disengagement for Ambiguous Human-Robot Stimuli. In: Agah, A., Cabibihan, JJ., Howard, A., Salichs, M., He, H. (eds) Social Robotics. ICSR 2016. Lecture Notes in Computer Science(), vol 9979. Springer, Cham. https://doi.org/10.1007/978-3-319-47437-3_93

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  • DOI: https://doi.org/10.1007/978-3-319-47437-3_93

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47436-6

  • Online ISBN: 978-3-319-47437-3

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