Effects of the Surroundings in Human-Robot Interaction: Stereotypical Perception of Robots and Its Anthropomorphism | SpringerLink
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Effects of the Surroundings in Human-Robot Interaction: Stereotypical Perception of Robots and Its Anthropomorphism

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Design, Operation and Evaluation of Mobile Communications (HCII 2022)

Abstract

Stereotypes and scripts guide human perception and expectations in everyday life. Research has found that a robot’s appearance influences the perceived fit in different application domains (e.g. industrial or social) and that the role a robot is presented in predicts its perceived personality. However, it is unclear how the surroundings as such can elicit a halo effect leading to stereotypical perceptions. This paper presents the results of an experimental study in which 206 participants saw 8 cartoon pictures of the robot Pepper in different application domains in a within-subjects online study. Results indicate that the environment a robot is placed in has an effect on the users’ evaluation of the robot’s warmth, competence, status in society, competition, anthropomorphism, and morality. As the first impression has an effect on users’ expectations and evaluation of the robot and the interaction with it, the effect of the application scenarios has to be considered carefully.

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References

  1. Arntz, A., Eimler, S.C., Hoppe, H.U.: Augmenting the human-robot communication channel in shared task environments. In: Nolte, A., Alvarez, C., Hishiyama, R., Chounta, I.-A., Rodríguez-Triana, M.J., Inoue, T. (eds.) CollabTech 2020. LNCS, vol. 12324, pp. 20–34. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-58157-2_2

    Chapter  Google Scholar 

  2. Arntz, A., Eimler, S.C., Hoppe, H.U.: A virtual sandbox approach to studying the effect of augmented communication on human-robot collaboration. Front. Robot. AI 8 (2021)

    Google Scholar 

  3. Asch, S.E.: Forming impressions of personality. Psychol. Sci. Publ. Interest 41(3), 258–290 (1946)

    Google Scholar 

  4. Banks, J.: A perceived moral agency scale: development and validation of a metric for humans and social machines. Comput. Hum. Behav. 90, 363–371 (2019). https://doi.org/10.1016/j.chb.2018.08.028

    Article  Google Scholar 

  5. Bartneck, C., Croft, E., Kulic, D.: Measuring the anthropomorphism, animacy, likeability, perceived intelligence and perceived safety of robots. In: Proceedings of the Metrics for Human-Robot Interaction Workshop at the 3rd International Conference on Human-Robot Interaction (HRI 2008), pp. 37–44. IEEE (2008)

    Google Scholar 

  6. Bergmann, K., Eyssel, F., Kopp, S.: A second chance to make a first impression? How appearance and nonverbal behavior affect perceived warmth and competence of virtual agents over time. In: Nakano, Y., Neff, M., Paiva, A., Walker, M. (eds.) IVA 2012. LNCS (LNAI), vol. 7502, pp. 126–138. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33197-8_13

    Chapter  Google Scholar 

  7. Burgoon, J.K.: Interpersonal expectations, expectancy violations, and emotional communication. J. Lang. Soc. Psychol. 12(1–2), 30–48 (1993)

    Article  Google Scholar 

  8. Butler, R., Pruitt, Z., Wiese, E.: The effect of social context on the mind perception of robots. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 63, pp. 230–234. SAGE Publications, Los Angeles (2019)

    Google Scholar 

  9. Eagly, A.H., Karau, S.J.: Role congruity theory of prejudice toward female leaders. Psychol. Rev. 109(3), 573–598 (2002). https://doi.org/10.1037//0033-295x.109.3.573

  10. Eckes, T.: Paternalistic and envious gender stereotypes: testing predictions from the stereotype content model. Sex Roles 47(3), 99–114 (2002). https://doi.org/10.1023/A:1021020920715

    Article  Google Scholar 

  11. Eyssel, F., Hegel, F.: (S)he’s got the look: gender stereotyping of robots. J. Appl. Soc. Psychol. 42(9), 2213–2230 (2012). https://doi.org/10.1111/j.1559-1816.2012.00937.x

    Article  Google Scholar 

  12. Fiske, S.T., Cuddy, A.J., Glick, P.: Universal dimensions of social cognition: warmth and competence. Trends Cogn. Sci. 11(2), 77–83 (2007). https://doi.org/10.1016/j.tics.2006.11.005

    Article  Google Scholar 

  13. Fiske, S.T., Cuddy, A.J., Glick, P., Xu, J.: A model of (often mixed) stereotype content: competence and warmth respectively follow from perceived status and competition. J. Pers. Soc. Psychol. 82(6), 878–902 (2002). https://doi.org/10.1037//0022-3514.82.6.878

    Article  Google Scholar 

  14. Franke, T., Attig, C., Wessel, D.: A personal resource for technology interaction: development and validation of the affinity for technology interaction (ATI) scale. Int. J. Hum.-Comput. Interact. 35(6), 456–467 (2019). https://doi.org/10.1080/10447318.2018.1456150

    Article  Google Scholar 

  15. Joosse, M., Lohse, M., Pérez, J.G., Evers, V.: What you do is who you are: the role of task context in perceived social robot personality. In: Proceedings of the 2013 IEEE International Conference on Robotics and Automation, pp. 2134–2139. IEEE (2013)

    Google Scholar 

  16. Lohse, M., Hegel, F., Wrede, B.: Domestic applications for social robots: an online survey on the influence of appearance and capabilities. J. Phys. Agents 2(2), 21–32 (2008). https://doi.org/10.14198/JoPha.2008.2.2.04

  17. Mieczkowski, H., Liu, S.X., Hancock, J., Reeves, B.: Helping not hurting: applying the stereotype content model and bias map to social robotics. In: Proceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 222–229. IEEE (2019). https://doi.org/10.1109/HRI.2019.8673307

  18. Nass, C., Moon, Y.: Machines and mindlessness: social responses to computers. J. Soc. Issues 56(1), 81–103 (2000). https://doi.org/10.1111/0022-4537.00153

    Article  Google Scholar 

  19. Nass, C., Steuer, J., Tauber, E.R.: Computers are social actors. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 72–78 (1994)

    Google Scholar 

  20. Nisbett, R.E., Wilson, T.D.: The halo effect: evidence for unconscious alteration of judgments. J. Pers. Soc. Psychol. 35(4), 250–256 (1977). https://doi.org/10.1037/0022-3514.35.4.250

    Article  Google Scholar 

  21. Nowak, K.L., Fox, J.: Avatars and computer-mediated communication: a review of the definitions, uses, and effects of digital representations. Rev. Commun. Res. 6, 30–53 (2018). https://doi.org/10.12840/issn.2255-4165.2018.06.01.015

  22. Oliveira, R., Arriaga, P., Correia, F., Paiva, A.: The stereotype content model applied to human-robot interactions in groups. In: Proceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction, pp. 123–132. IEEE (2020)

    Google Scholar 

  23. Reeves, B., Nass, C.: The Media Equation: How People Treat Computers, Television, and New Media like Real People and Places. Cambridge University Press, Cambridge (1996)

    Google Scholar 

  24. Roesler, E., Naendrup-Poell, L., Manzey, D., Onnasch, L.: Why context matters: the influence of application domain on preferred degree of anthropomorphism and gender attribution in human-robot interaction. Int. J. Soc. Robot. 1–12 (2022). https://doi.org/10.1007/s12369-021-00860-z

  25. Savela, N., Turja, T., Oksanen, A.: Social acceptance of robots in different occupational fields: a systematic literature review. Int. J. Soc. Robot. 10(4), 493–502 (2017). https://doi.org/10.1007/s12369-017-0452-5

    Article  Google Scholar 

  26. Seiler, R., Schär, A.: Chatbots, conversational interfaces, and the stereotype content model. In: Proceedings of the 54th Hawaii International Conference on System Sciences, pp. 1860–1867 (2021)

    Google Scholar 

  27. Syrdal, D.S., Dautenhahn, K., Woods, S.N., Walters, M.L., Koay, K.L.: Looking good? Appearance preferences and robot personality inferences at zero acquaintance. In: AAAI Spring Symposium: Multidisciplinary Collaboration for Socially Assistive Robotics, vol. 86, pp. 230–234. American Association for Artificial Intelligence (2007)

    Google Scholar 

  28. Yamashita, Y., Ishihara, H., Ikeda, T., Asada, M.: Investigation of causal relationship between touch sensations of robots and personality impressions by path analysis. Int. J. Soc. Robot. 11(1), 141–150 (2018). https://doi.org/10.1007/s12369-018-0483-6

    Article  Google Scholar 

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Acknowledgments

The presented work was partly supported by the Institute of Positive Computing (322-8.03.04-127491) funded by the Federal Ministry of Education and Research Germany. The authors thank all participants, as well as colleagues for their support: Elias Kyewski, Pasquale Hinrichs, Anna-Marie Schweizer, Lara Oldach, Noémi Tschiesche, Uwe Handmann. Presentation of this work is funded by the initiative for quality improvement in teaching of the Institute of Computer Science.

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Correspondence to Carolin Straßmann .

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Straßmann, C., Eimler, S.C., Kololli, L., Arntz, A., van de Sand, K., Rietz, A. (2022). Effects of the Surroundings in Human-Robot Interaction: Stereotypical Perception of Robots and Its Anthropomorphism. In: Salvendy, G., Wei, J. (eds) Design, Operation and Evaluation of Mobile Communications. HCII 2022. Lecture Notes in Computer Science, vol 13337. Springer, Cham. https://doi.org/10.1007/978-3-031-05014-5_30

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  • DOI: https://doi.org/10.1007/978-3-031-05014-5_30

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