Models of (Often) Ambivalent Robot Stereotypes
| Autor: | Giulia Perugia, Latisha Boor, Laura van der Bij, Okke Rikmenspoel, Robin Foppen, Stefano Guidi |
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| Přispěvatelé: | Human Technology Interaction, Industrial Engineering and Innovation Sciences |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | HRI '23: Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, 428-436 STARTPAGE=428;ENDPAGE=436;TITLE=HRI '23: Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction |
| DOI: | 10.1145/3568162.3576981 |
| Popis: | This study focused on investigating the content, structure, and predictors of robots' stereotypes. We involved 120 participants in an online study and asked them to rate 80 robots on communion, agency, suitability for female and suitability for male tasks. In line with the stereotype content model, we discovered that robots' stereotypes are described by two dimensions, communion and agency, which combine to form univalent (e.g., low communion/low agency), as well as ambivalent clusters (e.g., low communion/high agency). Moreover, we found out that a robot's stereotypical appearance has a role in activating stereotypes. Indeed, in our study, female robots featuring appearance cues socio-culturally associated with femininity (e.g., eyelashes or apparel) were perceived as more communal, and juvenile robots featuring appearance cues tapping into the baby schema (e.g., cartoony eyes) were perceived as more communal, less agentic, and less suited to perform tasks. Given the renowned relationship between stereotyping, prejudice and discrimination, the causal link between appearance and stereotyping we establish in this paper can help HRI researchers disentangle the relation between robots' design and people's behavioral tendencies towards them, including proneness to harm. |
| Databáze: | OpenAIRE |
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