De'Aira Bryant
ABSTRACT
The attribution of human-like characteristics onto humanoid robots has become a common practice in Human-Robot Interaction by designers and users alike. Robot gendering, the attribution of gender onto a robotic platform via voice, name, physique, or other features is a prevalent technique used to increase aspects of user acceptance of robots. One important factor relating to acceptance is user trust. As robots continue to integrate themselves into common societal roles, it will be critical to evaluate user trust in the robot's ability to perform its job. This paper examines the relationship among occupational gender-roles, user trust and gendered design features of humanoid robots. Results from the study indicate that there was no significant difference in the perception of trust in the robot's competency when considering the gender of the robot. This expands the findings found in prior efforts that suggest performance-based factors have larger influences on user trust than the robot's gender characteristics. In fact, our study suggests that perceived occupational competency is a better predictor for human trust than robot gender or participant gender. As such, gendering in robot design should be considered critically in the context of the application by designers. Such precautions would reduce the potential for robotic technologies to perpetuate societal gender stereotypes.
Supplemental Material
- Savela, N., Turja, T. and Oksanen, A., 2018. Social acceptance of robots in different occupational fields: A systematic literature review. International Journal of Social Robotics, 10(4), pp.493--502.Google Scholar
Cross Ref
- Hancock, P.A., Billings, D.R., Schaefer, K.E., Chen, J.Y., De Visser, E.J. and Parasuraman, R., 2011. A meta-analysis of factors affecting trust in human-robot interaction. Human factors, 53(5), pp.517--527.Google Scholar
- Bernotat, J., Eyssel, F. and Sachse, J., 2017, November. Shape it--the influence of robot body shape on gender perception in robots. In International Conference on Social Robotics (pp. 75--84). Springer, Cham.Google Scholar
- Robertson, J., 2010. Gendering humanoid robots: Robo-sexism in Japan. Body & Society, 16(2), pp.1--36.Google ScholarCross Ref
- Fridin, M. and Belokopytov, M., 2014. Acceptance of socially assistive humanoid robot by preschool and elementary school teachers. Computers in Human Behavior, 33, pp.23--31.Google ScholarDigital Library
- Ye, H., Jeong, H., Zhong, W., Bhatt, S., Izzetoglu, K., Ayaz, H. and Suri, R., 2019, July. The Effect of Anthropomorphization and Gender of a Robot on Human-Robot Interactions. In International Conference on Applied Human Factors and Ergonomics (pp. 357--362). Springer, Cham.Google Scholar
- Rea, D.J., Wang, Y. and Young, J.E., 2015, October. Check your stereotypes at the door: an analysis of gender typecasts in social human-robot interaction. In International Conference on Social Robotics (pp. 554--563). Springer, Cham.Google Scholar
- Eyssel, F. and Hegel, F., 2012. (s)he's got the look: Gender stereotyping of robots 1. Journal of Applied Social Psychology, 42(9), pp.2213--2230.Google ScholarCross Ref
- Ghazali, A.S., Ham, J., Barakova, E.I. and Markopoulos, P., 2018. Effects of robot facial characteristics and gender in persuasive human-robot interaction. Frontiers in Robotics and AI, 5, p.73.Google ScholarCross Ref
- Kuchenbrandt, D., Häring, M., Eichberg, J., Eyssel, F. and André, E., 2014. Keep an eye on the task! How gender typicality of tasks influence human--robot interactions. International Journal of Social Robotics, 6(3), pp.417--427.Google ScholarCross Ref
- Nomura, T., 2017. Robots and gender. Gender and the Genome, 1(1), pp.18--26.Google ScholarCross Ref
- Crowelly, C.R., Villanoy, M., Scheutzz, M. and Schermerhornz, P., 2009, October. Gendered voice and robot entities: perceptions and reactions of male and female subjects. In 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 3735--3741). IEEE.Google Scholar
- Tay, B., Jung, Y., & Park, T. (2014). When stereotypes meet robots: the double-edge sword of robot gender and personality in human--robot interaction. Computers in Human Behavior, 38, 75--84.Google ScholarDigital Library
- Le Deist, F.D. and Winterton, J., 2005. What is competence?. Human resource development international, 8(1), pp.27--46.Google Scholar
- Chita-Tegmark, M., Lohani, M. and Scheutz, M., 2019, March. Gender effects in perceptions of robots and humans with varying emotional intelligence. In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (pp. 230--238). IEEE.Google Scholar
- McGinn, C. and Torre, I., 2019, March. Can you tell the robot by the voice? An exploratory study on the role of voice in the perception of robots. In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (pp. 211--221). IEEE.Google Scholar
- Cameron, D., Millings, A., Fernando, S., Collins, E.C., Moore, R., Sharkey, A., Evers, V. and Prescott, T., 2018. The effects of robot facial emotional expressions and gender on child--robot interaction in a field study. Connection Science, 30(4), pp.343--361.Google ScholarCross Ref
- Jewell, C.I., Elprama, S.A., Jacobs, A., Esteban, P.G., Bagheri, E. and Vanderborght, B., 2019, March. Why Children Prefer Extrovert or Introvert Robots: A Pilot Study Using Pairwise Robot Comparison. In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (pp. 590--591). IEEE.Google Scholar
- He, J.C., Kang, S.K., Tse, K. and Toh, S.M., 2019. Stereotypes at work: Occupational stereotypes predict race and gender segregation in the workforce. Journal of Vocational Behavior, p.103318.Google ScholarCross Ref
- Gerdes, E.P. and Garber, D.M., 1983. Sex bias in hiring: Effects of job demands and applicant competence. Sex Roles, 9(3), pp.307--319.Google ScholarCross Ref
- Rosen, B. and Jerdee, T.H., 1974. Influence of sex role stereotypes on personnel decisions. Journal of Applied Psychology, 59(1), p.9.Google ScholarCross Ref
- Reskin, B.F. and Roos, P.A., 2009. Job queues, gender queues: Explaining women's inroads into male occupations.Google Scholar
- Mundy, L., 2018. Code Girls: The True Story of the American Women Who Secretly Broke Codes in World War II (Young Readers Edition). Little, Brown Books for Young Readers.Google Scholar
- Siegel, M., Breazeal, C. and Norton, M.I., 2009, October. Persuasive robotics: The influence of robot gender on human behavior. In 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 2563--2568). IEEE.Google Scholar
- He, J.C., Kang, S.K., Tse, K. and Toh, S.M., 2019. Stereotypes at work: Occupational stereotypes predict race and gender segregation in the workforce. Journal of Vocational Behavior, p.103318.Google ScholarCross Ref
- Wang, Y. and Young, J.E., 2014, May. Beyond pink and blue: Gendered attitudes towards robots in society. In Proceedings of Gender and IT Appropriation. Science and Practice on Dialogue-Forum for Interdisciplinary Exchange (p. 49). European Society for Socially Embedded Technologies.Google Scholar
- Labor Force Statistics from the Current U.S. Population Survey. US Department of Labor's Bureau of Labor and Statistics. https://www.bls.gov/cps/cpsaat11.htmGoogle Scholar
- Humphries, W. 2014. It's really no joke. Ozy: The Daily Dose. https://www.ozy.com/acumen/stand-ups-gender-gap/4661Google Scholar
- Pandey, A.K., Gelin, R. and Robot, A.M.P.S.H., 2018. Pepper: The First Machine of Its Kind. IEEE Robotics & Automation Magazine, 25(3), pp.40--48.Google ScholarCross Ref
- https://www.meredithkachel.com/gender-and-comedyGoogle Scholar
- https://www.womenincomedy.org/Google Scholar
- Bartneck, C., Yogeeswaran, K., Ser, Q.M., Woodward, G., Sparrow, R., Wang, S. and Eyssel, F., 2018, February. Robots and racism. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (pp. 196--204). ACM.Google Scholar
- Ogunyale, T., Bryant, D.A. and Howard, A., 2018. Does Removing Stereotype Priming Remove Bias? A Pilot Human-Robot Interaction Study. arXiv preprint arXiv:1807.00948.Google Scholar
- Kay, M., Matuszek, C. and Munson, S.A., 2015, April. Unequal representation and gender stereotypes in image search results for occupations. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 3819--3828). ACM.Google Scholar
- Kessler, T.T., Larios, C., Walker, T., Yerdon, V. and Hancock, P.A., 2017. A comparison of trust measures in human--robot interaction scenarios. In Advances in Human Factors in Robots and Unmanned Systems (pp. 353--364). Springer, Cham.Google Scholar
- Tamagawa, R., Watson, C.I., Kuo, I.H., MacDonald, B.A. and Broadbent, E., 2011. The effects of synthesized voice accents on user perceptions of robots. International Journal of Social Robotics, 3(3), pp.253--262.Google ScholarCross Ref
- Goetz, J., Kiesler, S. and Powers, A., 2003, November. Matching robot appearance and behavior to tasks to improve human-robot cooperation. In The 12th IEEE International Workshop on Robot and Human Interactive Communication, 2003. Proceedings. ROMAN 2003. (pp. 55--60). Ieee.Google Scholar
- Heerink, M., Krose, B., Evers, V. and Wielinga, B., 2009, September. Measuring acceptance of an assistive social robot: a suggested toolkit. In RO-MAN 2009-The 18th IEEE International Symposium on Robot and Human Interactive Communication (pp. 528--533). IEEE.Google Scholar
Index Terms
- Why Should We Gender?: The Effect of Robot Gendering and Occupational Stereotypes on Human Trust and Perceived Competency
Recommendations
Robot Gendering: Influences on Trust, Occupational Competency, and Preference of Robot Over Human
CHI EA '20: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing SystemsThis paper presents an investigation into the differences found in participants' comfort levels with using new humanoid robots in addition to the tendency to give a gender to a robot designed to be gender neutral. These factors were used to examine ...
'If you sound like me, you must be more human': on the interplay of robot and user features on human-robot acceptance and anthropomorphism
HRI '12: Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot InteractionIn an experiment we manipulated a robot's voice in two ways: First, we varied robot gender; second, we equipped the robot with a human-like or a robot-like synthesized voice. Moreover, we took into account user gender and tested effects of these factors ...
(Ir)relevance of Gender?: On the Influence of Gender Stereotypes on Learning with a Robot
HRI '17: Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot InteractionEducation research has documented a trend that reflects gender-based differences in the choice of fields of study. This, in turn, contributes to an imbalance in the representation of men and women in particular professions: In educational contexts, ...
Comments