When Stereotypes Meet Robots: The Effect of Gender Stereotypes on People’s Acceptance of a Security Robot

  • Benedict Tiong Chee Tay
  • Taezoon Park
  • Younbo Jung
  • Yeow Kee Tan
  • Alvin Hong Yee Wong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8019)


A recent development of social robotics suggests the integration of human characteristics social robots, which allows a more natural interaction between users and these social robots targeting better task performance and greater user acceptance to such social robots. It is interesting to note that the recent successful integration of human characteristics has brought an overarching research paradigm, known as Computers Are Social Actors (CASA) theory which suggests that people react and respond to computers and robots, often similar to the way they treat another social entities. Based on the research paradigm of CASA theory, this study further examined the impact of gender-related role stereotypes on the assessment of a social robot in a particular occupation. Though previous research in social science found that stereotyping makes a significant influence on personal decisions, involving career promotion, development, and supervision, as well as personal competence evaluations, limited insights has been found in HRI research. A between-subject experiment was conducted with 40 participants (gender balanced) at a public university in Singapore to investigate the effect of gender-related role stereotypes on user acceptance of a social robot as a security guard. Largely within our expectations, the results also showed that users perceived the security robot with matching gender-related role stereotypes more useful and acceptable than the mismatched security robot as a second-degree social response.


Social Robots Human—Robot Interactions User Acceptance Gender Stereotypes 


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  1. 1.
    Asch, S.E.: Forming impressions of personality. Journal of Abnormal and Social Psychology 41, 258–290 (1946)CrossRefGoogle Scholar
  2. 2.
    Bargh, J.A.: The cognitive monster: The case against the controllability of automatic stereotype effects. In: Chaiken, S., Trope, Y. (eds.) Dual Process Theories in Social Psychology, pp. 361–382. Guilford, New York (1999)Google Scholar
  3. 3.
    Bargh, J.A., Chen, M., Burrows, L.: Automaticity of social behavior: Direct effects of trait construct and stereotype activation on action. Journal of Personality and Social Psychology 71(2), 230–244 (1996), doi:10.1037/0022-3514.71.2.230CrossRefGoogle Scholar
  4. 4.
    Breazeal, C.: Toward sociable robots. Robotics and Autonomous Systems 42(3-4), 167–175 (2003), doi:10.1016/S0921-8890(02)00373-1CrossRefzbMATHGoogle Scholar
  5. 5.
    Brewer, M.B.: A dual process model of impression formation. In: Srull, T.K., Wyer Jr., R.S. (eds.) A Dual Process Model of Impression Formation, pp. 1–36. Lawrence Erlbaum Associates, Inc., Hillsdale (1988)Google Scholar
  6. 6.
    Carpenter, J., Davis, J., Erwin-Stewart, N., Lee, T., Bransford, J., Vye, N.: Gender Representation and Humanoid Robots Designed for Domestic Use. International Journal of Social Robotics 1(3), 261–265 (2009), doi:10.1007/s12369-009-0016-4CrossRefGoogle Scholar
  7. 7.
    Cejka, M.A., Eagly, A.H.: Gender-stereotypic images of occupations correspond to the sex segregation of employment. Personality and Social Psychology Bulletin 25(4), 413–423 (1999), doi:10.1177/0146167299025004002CrossRefGoogle Scholar
  8. 8.
    Crowther, B., More, D.M.: Occupational stereotyping on initial impressions. Journal of Vocational Behavior 2(1), 87–94 (1972), doi:10.1016/0001-8791(72)90010-3CrossRefGoogle Scholar
  9. 9.
    Dautenhahn, K., Woods, S., Kaouri, C., Walters, M.L., Kheng Lee, K., Werry, I.: What is a robot companion - friend, assistant or butler? In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1192–1197 (2005)Google Scholar
  10. 10.
    Devine, P.G.: Stereotypes and prejudice: Their automatic and controlled components. Journal of Personality and Social Psychology 56, 680–690 (1989)CrossRefGoogle Scholar
  11. 11.
    Dunn, R.A., Guadagno, R.E.: My avatar and me – Gender and personality predictors of avatar-self discrepancy. Computers in Human Behavior 28(1), 97–106 (2012)CrossRefGoogle Scholar
  12. 12.
    Edsinger, A., Reilly, U.-M.O., Breazeal, C.: Personality through faces for humanoid robots. Proceedings of the 9th IEEE International Workshop on Paper Presented at the Robot and Human Interactive Communication, RO-MAN 2000 (2000)Google Scholar
  13. 13.
    Eyssel, F., Hegel, F.: (S)he’s got the look: gender stereotyping of robots. Journal of Applied Social Psychology 42(9), 2213–2230 (2012)Google Scholar
  14. 14.
    Ezer, N., Fisk, A.D., Rogers, W.A.: Attitudinal and intentional acceptance of domestic robots by younger and older adults. In: Stephanidis, C. (ed.) UAHCI 2009, Part II. LNCS, vol. 5615, pp. 39–48. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  15. 15.
    Fiske, S.T., Taylor, S.E.: Social Cognition, 2nd edn. McGraw-Hill, Inc. (1991)Google Scholar
  16. 16.
    Fong, T., Nourbakhsh, I., Dautenhahn, K.: A survey of socially interactive robots. Robotics and Autonomous Systems 42(3-4), 143–166 (2003)CrossRefzbMATHGoogle Scholar
  17. 17.
    Garrett, C.S., Ein, P.L., Tremaine, L.: The development of gender stereotyping of adult occupations in elementary school children. Child Development 48(2), 507–512 (1977)CrossRefGoogle Scholar
  18. 18.
    Gerdes, E.P., Garber, D.M.: Sex bias in hiring: Effects of job demands and applicant competence. Sex Roles 9(3), 307–319 (1983), doi:10.1007/bf00289666CrossRefGoogle Scholar
  19. 19.
    Glick, P., Zion, C., Nelson, C.: What mediates sex discrimination in hiring decisions? Journal of Personality and Social Psychology 55(2), 178–186 (1988)CrossRefGoogle Scholar
  20. 20.
    Goldberg, P.: Are women prejudiced against women? Society 5(5), 28–30 (1968)CrossRefGoogle Scholar
  21. 21.
    Grant, P.R., Holmes, J.G.: The integration of implicit personality theory schemas and stereotype images. Social Psychology Quarterly 44(2), 107–115 (1981)CrossRefGoogle Scholar
  22. 22.
    Groom, V.: What’s the best role for a robot? Cybernetic models of existing and proposed human-robot interaction structures. Paper Presented at the Proceedings of the International Conference on Informatics in Control, Automation, and Robotics (ICINCO) 2008, Funchal, Portugal (2008)Google Scholar
  23. 23.
    Hudlicka, E., Becker-Asano, C., Payr, S., Fischer, K., Ventura, R., Leite, I., von Scheve, C.: Social interaction with robots and agents: Where do we stand, where do we go? 3rd International Conference on Paper Presented at the Affective Computing and Intelligent Interaction and Workshops, ACII 2009, September 10-12 (2009)Google Scholar
  24. 24.
    Kim, H., Kwak, S.S., Kim, M.: Personality design of sociable robots by control of gesture design factors. The 17th IEEE International Symposium on Paper Presented at the Robot and Human Interactive Communication, RO-MAN (2008)Google Scholar
  25. 25.
    Lee, K.M., Peng, W., Yan, C., Jin, S.: Can robots manifest personality?: An empirical test of personality recognition, social Responses, and social Presence in human-robot interaction. Journal of Communication (56), 754–772 (2006)Google Scholar
  26. 26.
    Levy, D.A., Kaler, S.R., Schall, M.: An empirical investigation of role schemata: Occupations and personality characteristics. Psychological Reports 63(1), 3–14 (1988)CrossRefGoogle Scholar
  27. 27.
    Li, J., Chignell, M.: Birds of a feather: How personality influences blog writing and reading. International Journal of Human-Computer Studies 68(9), 589–602 (2010)CrossRefGoogle Scholar
  28. 28.
    Linville, P.W., Jones, E.E.: Polarized appraisals of out-group members. Journal of Personality and Social Psychology 38(5), 689–703 (1980)CrossRefGoogle Scholar
  29. 29.
    Martin, C.L., Ruble, D.: Children’s search for gender cues: cognitive perspectives on gender development. Current Directions in Psychological Science (2), 67 (2004)Google Scholar
  30. 30.
    McCauley, C., Thangavelu, K.: Individual differences in sex stereotyping of occupations and personality traits. Social Psychology Quarterly 54(3), 267–279 (1991)CrossRefGoogle Scholar
  31. 31.
    McLean, H.M., Kalin, R.: Congruence between self-image and occupational stereotypes in students entering gender-dominated occupations. Canadian Journal of Behavioural Science/Revue Canadienne des Sciences du Comportement 26(1), 142–162 (1994)CrossRefGoogle Scholar
  32. 32.
    Mori, M.: The Uncanny Valley. Enery 7, 33–35 (1970)Google Scholar
  33. 33.
    Muscanell, N.L., Guadagno, R.E.: Make new friends or keep the old. Computers in Human Behavior 28(1), 107–112 (2012)CrossRefGoogle Scholar
  34. 34.
    Nass, C., Moon, Y., Carney, P.: Are people polite to computers? Responses to computer-based interviewing systems. Journal of Applied Social Psychology 29(5), 1093–1110 (1999)CrossRefGoogle Scholar
  35. 35.
    Nass, C., Steuer, J., Tauber, E.R.: Computer are social actors. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems: Celebrating Interdependence, pp. 72–78. ACM (1994)Google Scholar
  36. 36.
    Population Division UN. World Population Ageing: 1950-2050 (2000), (retrieved February 14, 2013)
  37. 37.
    Powers, A., Kramer, A.D.I., Lim, S., Kuo, J., Sau-lai, L., Kiesler, S.: Eliciting information from people with a gendered humanoid robot. IEEE International Workshop on Paper Presented at the Robot and Human Interactive Communication, ROMAN 2005, August 13-15 (2005)Google Scholar
  38. 38.
    Ray, C., Mondada, F., Siegwart, R.: What do people expect from robots? IEEE/RSJ International Conference on Paper Presented at the Intelligent Robots and Systems, IROS 2008, September 22-26 (2008)Google Scholar
  39. 39.
    Reeves, B., Nass, C.: The media equation: How people treat computers, television and new media like real people and places. Cambridge University Press, New York (1996)Google Scholar
  40. 40.
    Robertson, J.: Gendering humanoid robots: Robo-sexism in Japan. Body & Society 16(2), 1–36 (2010), doi:10.1177/1357034x10364767CrossRefGoogle Scholar
  41. 41.
    Rokeach, M., Mezei, L.: Race and shared belief as factors in social choice. Science 151(3707), 167–172 (1966)CrossRefGoogle Scholar
  42. 42.
    Rosen, B., Jerdee, T.H.: The influence of sex-role stereotypes on evaluations of male and female supervisory behavior. Journal of Applied Psychology 57(1), 44–48 (1973)CrossRefGoogle Scholar
  43. 43.
    Rosen, B., Jerdee, T.H.: Effects of applicant’s sex and difficulty of job on evaluations of candidates for managerial positions. Journal of Applied Psychology 59(4), 511–512 (1974a), doi:10.1037/h0037323CrossRefGoogle Scholar
  44. 44.
    Rosen, B., Jerdee, T.H.: Influence of sex role stereotypes on personnel decisions. Journal of Applied Psychology 59(1), 9–14 (1974b), doi:10.1037/h0035834CrossRefGoogle Scholar
  45. 45.
    Schneider, D.J.: The Psychology of Stereotyping. The Guilford Press, New York (2004)Google Scholar
  46. 46.
    Shinar, E.H.: Sexual stereotypes of occupations. Journal of Vocational Behavior 7(1), 99–111 (1975), doi:10.1016/0001-8791(75)90037-8CrossRefMathSciNetGoogle Scholar
  47. 47.
    Siegel, M., Breazeal, C., Norton, M.I.: Persuasive Robotics: The influence of robot gender on human behavior. IEEE/RSJ International Conference on Paper Presented at the Intelligent Robots and Systems, IROS 2009, October 10-15 (2009)Google Scholar
  48. 48.
    Stangor, C., Schaller, M.: Stereotypes as Individual and Collective Representations. In: Stangor, C. (ed.) Stereotypes and Prejudice: Essential Readings, pp. 64–85. Psychology Press, Philadelphia (2000)Google Scholar
  49. 49.
    Streiff, S., Tschan, F., Hunziker, S., Buehlmann, C., Semmer, N.K., Hunziker, P., Marsch, S.: Leadership in medical emergencies depends on gender and personality. Simulation in Healthcare 6(2), 78 (2011)CrossRefGoogle Scholar
  50. 50.
    Swann, W.B.: Quest for accuracy in person perception: A matter of pragmatics. Psychological Review 91(4), 457–477 (1984), doi:10.1037/0033-295x.91.4.457CrossRefGoogle Scholar
  51. 51.
    Swim, J., Borgida, E., Maruyama, G., Myers, D.G.: Joan McKay versus John McKay. Psychological Bulletin 105(3), 409–429 (1989)CrossRefGoogle Scholar
  52. 52.
    Tapus, A., Tapus, C., Matarić, M.J.: User-robot personality matching and assistive robot behavior adaptation for post-stroke rehabilitation therapy. Intelligent Service Robotics 1(2), 169–183 (2008)CrossRefGoogle Scholar
  53. 53.
    Triandis, H.C.: Differential perception of certain jobs and people by managers, clerks, and workers in industry. Journal of Applied Psychology 43(4), 221–225 (1959)CrossRefGoogle Scholar
  54. 54.
    Walker, K.F.: A study of occupational stereotypes. Journal of Applied Psychology 42(2), 122–124 (1958), doi:10.1037/h0045472CrossRefGoogle Scholar
  55. 55.
    Woods, S., Dautenhahn, K., Kaouri, C., Boekhorst, R., Kheng Lee, K.: Is this robot like me? Links between human and robot personality traits. 2005 5th IEEE-RAS International Conference on Paper Presented at the Humanoid Robots, December 5-5 (2005)Google Scholar
  56. 56.
    Woods, S.A., Hampson, S.E.: Predicting adult occupational environments from gender and childhood personality traits. Journal of Applied Psychology 95(6), 1045–1057 (2010)CrossRefGoogle Scholar
  57. 57.
    World Health Organization, The World Health Report 2006: Working together for health (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Benedict Tiong Chee Tay
    • 1
  • Taezoon Park
    • 1
  • Younbo Jung
    • 2
  • Yeow Kee Tan
    • 3
  • Alvin Hong Yee Wong
    • 3
  1. 1.Division of Systems and Engineering Management, School of Mechanical & Aerospace EngineeringNanyang Technological UniversitySingapore
  2. 2.Division of Communication Research, Wee Kim Wee School of Communication and InformationNanyang Technological UniversitySingapore
  3. 3.Institute of Infocomm Research, Agency for Science, Technology and Research (A*STAR)Singapore

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