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Ambivalent Stereotypes Towards Gendered Robots: The (Im)mutability of Bias Towards Female and Neutral Robots

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Social Robotics (ICSR 2022)

Abstract

Many studies have investigated the effect of robot genderedness on the attribution of gender stereotypes to a robot, often with mixed results. This paper aims to overcome some of the limitations of previous research. We adopted a mixed study design with stereotypical trait type (communion vs. agency) or task type (stereotypical female vs. stereotypical male) and robot genderedness (female vs. male vs. neutral) as within-subjects factors, and participant gender (men vs. women) as between-subjects factor. We asked participants to rate 24 robots (8 per category) in terms of their perceived communion, agency, and suitability for stereotypical female and male tasks. The results disclosed that female robots activate paternalistic stereotypes (higher communion than agency, higher suitability for female tasks than male tasks), while male robots do not. Moreover, they reveal that the ambivalence of these stereotypes is stronger in men than in women. Even more interestingly, our analyses showed that neutral robots activate paternalistic stereotypes in men and envious stereotypes (higher agency than communion) in women. This last finding is particularly relevant as it suggests that gender neutrality is not enough to safeguard robots from harmful biases.

This work is part of the research programme Ethics of Socially Disruptive Technologies, which is funded through the Gravitation programme of the Dutch Ministry of Education, Culture, and Science and the Netherlands Organization for Scientific Research (NWO grant number 024.004.031).

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Notes

  1. 1.

    Not yet publicly available at the time of publication.

  2. 2.

    The higher masculinity cut-off score being necessary given most of the robots in the original study were perceived as male.

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Correspondence to Giulia Perugia .

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Guidi, S., Boor, L., van der Bij, L., Foppen, R., Rikmenspoel, O., Perugia, G. (2022). Ambivalent Stereotypes Towards Gendered Robots: The (Im)mutability of Bias Towards Female and Neutral Robots. In: Cavallo, F., et al. Social Robotics. ICSR 2022. Lecture Notes in Computer Science(), vol 13818. Springer, Cham. https://doi.org/10.1007/978-3-031-24670-8_54

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  • DOI: https://doi.org/10.1007/978-3-031-24670-8_54

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