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The Peculiarities of Robot Embodiment (EmCorp-Scale): Development, Validation and Initial Test of the Embodiment and Corporeality of Artificial Agents Scale

Published:26 February 2018Publication History

ABSTRACT

We propose a new theoretical framework assuming that embodiment effects in HAI and HRI are mediated by users' perceptions of an artificial entity's body-related capabilities. To enable the application of our framework to foster more theoretical-driven research, we developed a new self-report measurement that assesses bodilyrelated perceptions of the embodiment and corporeality - which we reveal as not being a binary characteristic of artificial entities. For the development and validation of the new scale we conducted two surveys and one video-based experiment. Exploratory factor analysis reveal a four-factorial solution with good reliability (Study 2, n = 442), which was confirmed via confirmatory factor analysis (Study 3, n = 260). In addition, we present first insights into the explanatory power of the scale: We reveal that humans? perceptions of an artificial entity's capabilities vary between virtual and physical embodiments, and that the evaluation of the artificial counterpart can be explained through the perceived capabilities. Practical applications and future research lines are discussed.

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References

  1. Wilma A. Bainbridge, Justin W. Hart, Elizabeth S. Kim, and Brian Scassellati. 2011. The Benefits of Interactions with Physically Present Robots over VideoDisplayed Agents. International Journal of Social Robotics 3, 1 (2011), 41--52.Google ScholarGoogle ScholarCross RefCross Ref
  2. M. S. Bartlett. 1937. Properties of Sufficiency and Statistical Tests. Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences 160, 901 (1937), 268--282.Google ScholarGoogle ScholarCross RefCross Ref
  3. Christoph Bartneck. 2003. Interacting with an embodied emotional character. In Proceedings of the International Conference on Designing Pleasurable Products and Interfaces. ACM Press, New York, NY, 55--60. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Colleen M. Carpinella, Alisa B. Wyman, Michael A. Perez, and Steven J. Stroessner. 2017. The Robotic Social Attributes Scale (RoSAS). In Proceedings of the 2017 ACMIEEE International Conference on Human-Robot Interaction, Bilge Mutlu (Ed.). ACM, {S.l.}, 254--262. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Juan Fasola and Maja Mataric. 2013. A socially assistive robot exercise coach for the elderly. Journal of Human-Robot Interaction 2, 2 (2013), 3--32. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Eamonn Ferguson and Tom Cox. 1993. Exploratory Factor Analysis: A Users' Guide. International Journal of Selection and Assessment 1, 2 (1993), 84--94.Google ScholarGoogle ScholarCross RefCross Ref
  7. Andy P. Field. 2009. Discovering statistics using SPSS: (and sex and drugs and rock and roll) (3 ed.). Sage Publications, Los Angeles {i.e. Thousand Oaks and Calif.} and London. {8} Kerstin Fischer, Katrin S. Lohan, and Kilian Foth. 2012. Levels of embodiment: Linguistic analyses of factors influencing HRI. In Proceedings of the 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI'12). 463--470. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Dai Hasegawa, Justine Cassell, and Kenji Araki. 2010. The Role of Embodiment and Perspective in Direction-Giving Systems. In AAAI Fall Symposium: Dialog with Robots.Google ScholarGoogle Scholar
  9. Laura Hoffmann and Nicole C. Krämer. 2013. Investigating the effects of physical and virtual embodiment in task-oriented and conversational contexts. International Journal of Human-Computer Studies 71, 7--8 (2013), 763--774. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. John L. Horn. 1965. A rationale and test for the number of factors in factor analysis. Psychometrika 30, 2 (1965), 179--185.Google ScholarGoogle ScholarCross RefCross Ref
  11. Li-tze Hu and Peter M. Bentler. 1999. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal 6, 1 (1999), 1--55.Google ScholarGoogle ScholarCross RefCross Ref
  12. Henry F. Kaiser. 1974. An index of factorial simplicity. Psychometrika 39, 1 (1974), 31--36.Google ScholarGoogle ScholarCross RefCross Ref
  13. Hiroko Kamide, Yasushi Mae, Koji Kawabe, Satoshi Shigemi, Masato Hirose, and Tatsuo Arai. 2012. New measurement of psychological safety for humanoid. In Proceedings of the seventh annual ACM/IEEE international conference on HumanRobot Interaction. ACM, 49--56. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Hiroko Kamide, Yasushi Mae, Tomohito Takubo, Kenichi Ohara, and Tatsuo Arai. 2014. Direct comparison of psychological evaluation between virtual and real humanoids: Personal space and subjective impressions. International Journal of Human-Computer Studies 72, 5 (2014), 451--459.Google ScholarGoogle ScholarCross RefCross Ref
  15. James Kennedy, Paul Baxter, and Tony Belpaeme. 2015. Comparing Robot Embodiments in a Guided Discovery Learning Interaction with Children. International Journal of Social Robotics 7, 2 (2015), 293--308.Google ScholarGoogle ScholarCross RefCross Ref
  16. C. D. Kidd and Cynthia L. Breazeal. 2004. Effect of a robot on user perceptions. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2004) (2004), 3559--3564.Google ScholarGoogle Scholar
  17. Sara B. Kiesler, Aaron Powers, Susan R. Fussell, and C. Torrey. 2008. Anthropomorphic Interactions with a Robot and Robot-Like Agent. Social Cognition 26, 2 (2008), 169--181.Google ScholarGoogle ScholarCross RefCross Ref
  18. Takanori Komatsu. 2010. Comparison an On-screen Agent with a Robotic Agent in an Everyday Interaction Style: How to Make Users React Toward an On-screen Agent as if They are Reacting Toward a Robotic Agent. In Human-robot interaction, Daisuke Chugo (Ed.). InTech, Vukovar, Croatia.Google ScholarGoogle Scholar
  19. Kwan Min Lee, Younbo Jung, Jaywoo Kim, and Sang Ryong Kim. 2006. Are physically embodied social agents better than disembodied social agents?: The effects of physical embodiment, tactile interaction, and people's loneliness in human--robot interaction. International Journal of Human-Computer Studies 64, 10 (2006), 962--973. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Iolanda Leite, André Pereira, Carlos Martinho, and Ana Paiva. 2008. Are emotional robots more fun to play with?. In Proceedings of the 17th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2008). IEEE, Piscataway, NJ, 77--82.Google ScholarGoogle ScholarCross RefCross Ref
  21. Jamy Li. 2015. The benefit of being physically present: A survey of experimental works comparing copresent robots, telepresent robots and virtual agents. International Journal of Human-Computer Studies 77 (2015), 23--37. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Jamy Li and Mark Chignell. 2011. Communication of Emotion in Social Robots through Simple Head and Arm Movements. International Journal of Social Robotics 3, 2 (2011), 125--142.Google ScholarGoogle ScholarCross RefCross Ref
  23. Gitta H. Lubke and Bengt O. Muthén. 2004. Applying Multigroup Confirmatory Factor Models for Continuous Outcomes to Likert Scale Data Complicates Meaningful Group Comparisons. Structural Equation Modeling: A Multidisciplinary Journal 11, 4 (2004), 514--534.Google ScholarGoogle ScholarCross RefCross Ref
  24. J. C. McCroskey, P.R Hamilton, and A.N Weiner. 1974. The effect of interaction behavior on source credibility, homophily, and interpersonal attraction. Human Communication Research 1, 1 (1974), 42--52.Google ScholarGoogle ScholarCross RefCross Ref
  25. John McIver and Edward G. Carmines. 1981. Unidimensional scaling. Sage.Google ScholarGoogle Scholar
  26. Tatsuya Nomura, Tomohiro Suzuki, Takayuki Kanda, and Kensuke Kato. 2006. Measurement of negative attitudes toward robots. Interaction Studies 7, 3 (2006), 437--454.Google ScholarGoogle ScholarCross RefCross Ref
  27. Albert Satorra. 2000. Scaled and Adjusted Restricted Tests in Multi-Sample Analysis of Moment Structures. In Innovations in Multivariate Statistical Analysis, R. D. H. Heijmans, D. S. G. Pollock, and A. Satorra (Eds.). Advanced Studies in Theoretical and Applied Econometrics, Vol. 36. Springer US, Boston, MA, 233--247.Google ScholarGoogle Scholar
  28. Karin Schermelleh-Engel, Helfried Moosbrugger, and Hans Müller. 2003. Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of psychological research online 8, 2 (2003), 23--74.Google ScholarGoogle Scholar
  29. K. Shinozawa, F. Naya, J. Yamato, and K. Kogure. 2005. Differences in effect of robot and screen agent recommendations on human decision-making. International Journal of Human-Computer Studies 62, 2 (2005), 267--279. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. James Stevens. 2009. Applied multivariate statistics for the social sciences (5 ed.). Routledge, New York.Google ScholarGoogle Scholar
  31. Wayne F. Velicer, Andrew C. Peacock, and Douglas N. Jackson. 1982. A comparison of component and factor patterns: A Monte Carlo approach. Multivariate Behavioral Research 17, 3 (1982), 371--388.Google ScholarGoogle ScholarCross RefCross Ref
  32. Joshua Wainer, David J. Feil-Seifer, Dylan Shell, and Maja J. Matarić. 2007. Embodiment and human-robot interaction: A task-based perspective. In 16th IEEE International Conference on Robot & Human Interactive Communication. IEEE, Piscataway, N.J., 872--877.Google ScholarGoogle Scholar

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  1. The Peculiarities of Robot Embodiment (EmCorp-Scale): Development, Validation and Initial Test of the Embodiment and Corporeality of Artificial Agents Scale

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    • Published in

      cover image ACM Conferences
      HRI '18: Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction
      February 2018
      468 pages
      ISBN:9781450349536
      DOI:10.1145/3171221

      Copyright © 2018 ACM

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      Publication History

      • Published: 26 February 2018

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      HRI '18 Paper Acceptance Rate49of206submissions,24%Overall Acceptance Rate242of1,000submissions,24%

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