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Do Robots Distract us as much as Humans?: The Effect ofHuman-like Appearance and Perceptual Load

Published:01 April 2020Publication History

ABSTRACT

Attention is an important mechanism for solving certain tasks, but our environment can distract us via irrelevant information. As robots increasingly become part of our lives, one important question is whether they could distract us as much as humans do, and if so to what extent. To address this question, we conducted a study in which subjects were engaged in a central letter detection task. The task irrelevant distractors were pictures of three agents; a mechanical robot, a human-like robot, and a real human. We also manipulated the perceptual load to investigate whether the demands of the task influence how much these agents distract us. Our results show that robots distract people as much as humans, as demonstrated by significant increase in reaction times and decrease in task accuracy in the presence of agent distractors as compared to the situation when there was no distractor. However, we found that the task difficulty interacted with the human-likeness of the distractor agent. When the task was less demanding, the agent that distracted most was the most human-like agent, whereas when the task was more demanding, the least human-like agent distracted the most. These results not only provide insights about how to design humanoid robots but also sets as a great example of a fruitful collaboration between human-robot interaction and cognitive sciences.

References

  1. N. Lavie, S. Cox (1997). On the efficiency of attentional selection: Efficient visual search results in inefficient rejection of distraction. Psychological Science, 8, 395--398.Google ScholarGoogle ScholarCross RefCross Ref
  2. N. Lavie (2000). Selective attention and cognitive control: Dissociating attentional functions through different types of load. In Attention and performance, XVIII (S. Monsell, J. Driver (eds.)), pp. 175--194, MIT Press.Google ScholarGoogle Scholar
  3. N. Lavie, T. Ro, C. Russell (2003). The role of perceptual load in processing distractor faces. Psychological Science, 14 (5), 510--515.Google ScholarGoogle ScholarCross RefCross Ref
  4. N. Lavie (2005). Distracted and confused? Selective attention under load. Trends in Cognitive Sciences, 9 (2), 75--82.Google ScholarGoogle ScholarCross RefCross Ref
  5. S. Forster, N. Lavie (2008). Attentional capture by entirely irrelevant distractors. Visual Cognition, 16:2--3, 200--214.Google ScholarGoogle ScholarCross RefCross Ref
  6. N. Lavie (2010). Attention, distraction, and cognitive control under load. Current Directions in Psychological Science, 19 (3), 143--148.Google ScholarGoogle ScholarCross RefCross Ref
  7. M. Mori (1970). The uncanny valley. Energy, 7 (4), 33--35.Google ScholarGoogle Scholar
  8. A.P. Saygin, T. Chaminade, H. Ishiguro, J. Driver, C. Frith (2012). The thing that should not be: predictive coding and the uncanny valley in perceiving human and humanoid robot actions. Social Cognitive Affective Neuroscience, 7 (4), 413- 422.Google ScholarGoogle ScholarCross RefCross Ref
  9. B.A. Urgen, M. Kutas, A.P. Saygin (2018). Uncanny valley as a window into predictive processing in the social brain. Neuropsychologia, 114, 181--185.Google ScholarGoogle ScholarCross RefCross Ref
  10. A.X. Li, M. Florendo, L.E. Miller, H. Ishiguro, A.P. Saygin (2015). Robot form and motion influences social attention. 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Portland, USA.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. B.A. Urgen, S.Pehlivan, A.P.Saygin (2019). Distinct representations in occipito-temporal, parietal, and premotor cortex during action perception revealed by fMRI and computational modeling. Neuropsychologia, 127, 35--47.Google ScholarGoogle ScholarCross RefCross Ref

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    • Published in

      cover image ACM Conferences
      HRI '20: Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction
      March 2020
      702 pages
      ISBN:9781450370578
      DOI:10.1145/3371382

      Copyright © 2020 Owner/Author

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      • Published: 1 April 2020

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