Affiliation:
1. GESIS—Leibniz Institute for the Social Sciences, Germany
2. University of Passau, Germany
3. University of Bern, Switzerland
4. University of Zurich, Switzerland
5. University of Mannheim, Germany; Seeburg Castle University, Austria
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 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.
Funder
Deutsche Forschungsgemeinschaft
Friends of the Institute of Communication and Media Science (FKMB) at the University of Bern
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Subject
Sociology and Political Science,Communication
Cited by
4 articles.
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