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Representativeness and face-ism: Gender bias in image search
[journal article]
Abstract Implicit and explicit gender biases in media representations of individuals have long existed. Women are less likely to be represented in gender-neutral media content (representation bias), and their face-to-body ratio in images is often lower (face-ism bias). In this article, we look at representat... view more
Implicit and explicit gender biases in media representations of individuals have long existed. Women are less likely to be represented in gender-neutral media content (representation bias), and their face-to-body ratio in images is often lower (face-ism bias). In this article, we look at representativeness and face-ism in search engine image results. We systematically queried four search engines (Google, Bing, Baidu, Yandex) from three locations, using two browsers and in two waves, with gender-neutral (person, intelligent person) and gendered (woman, intelligent woman, man, intelligent man) terminology, accessing the top 100 image results. We employed automatic identification for the individual’s gender expression (female/male) and the calculation of the face-to-body ratio of individuals depicted. We find that, as in other forms of media, search engine images perpetuate biases to the detriment of women, confirming the existence of the representation and face-ism biases. In-depth algorithmic debiasing with a specific focus on gender bias is overdue.... view less
Keywords
picture; online service; proportion of women; algorithm; sex ratio; representation; search engine; experiment
Classification
Women's Studies, Feminist Studies, Gender Studies
Interactive, electronic Media
Free Keywords
Algorithm auditing; face-ism; gender bias; image search; search engines
Document language
English
Publication Year
2022
Page/Pages
p. 1-27
Journal
New Media & Society (2022)
DOI
https://doi.org/10.1177/14614448221100699
ISSN
1461-7315
Status
Published Version; peer reviewed
Licence
Creative Commons - Attribution 4.0
FundingGefördert durch die Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 491156185 / Funded by the German Research Foundation (DFG) - Project number 491156185