Exploring Gender-Expansive Categorization Options for Robots
| Autor: | Seaborn, Katie, Pennefather, Peter, Kotani, Haruki |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | CHI EA '22: CHI Conference on Human Factors in Computing Systems Extended Abstracts, April 2022, Article No.: 252 |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1145/3491101.3519646 |
| Popis: | Gender is increasingly being explored as a social characteristic ascribed to robots by people. Yet, research involving social robots that may be gendered tends not to address gender perceptions, such as through pilot studies or manipulation checks. Moreover, research that does address gender perceptions has been limited by a reliance on the human gender binary model of feminine and masculine, prescriptive response options, and/or researcher assumptions and/or ascriptions of participant gendering. In response, we conducted an online pilot categorization study (n=55) wherein we provided gender-expansive response options for rating four robots ranging across four levels of anthropomorphism. Findings indicate that people gender robots in diverse ways, and not necessarily in relation to the gender binary. Additionally, less anthropomorphic robots and the childlike humanoid robot were deemed masculine, while the iconic robot was deemed gender neutral, fluid, and/or ambiguous. We discuss implications for future work on all humanoid robots. Comment: Accepted at CHI EA '22 |
| Databáze: | arXiv |
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