Unequal Representation and Gender Stereotypes in Image Search Results for Occupations
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2015-04-18
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Matthew Kay, Cynthia Matuszek, Sean A. Munson, Unequal Representation and Gender Stereotypes in Image Search Results for Occupations, ACM CHI Conference on Human Factors in Computing Systems, Seoul, Korea, 10.1145/2702123.2702520, April 2015, https://dl.acm.org/citation.cfm?id=2702520
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This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.
Abstract
Information environments have the power to affect people's perceptions and behaviors. In this paper, we present the results of studies in which we characterize the gender bias present in image search results for a variety of occupations. We experimentally evaluate the effects of bias in image search results on the images people choose to represent those careers and on people's perceptions of the prevalence of men and women in each occupation. We find evidence for both stereotype exaggeration and systematic underrepresentation of women in search results. We also find that people rate search results higher when they are consistent with stereotypes for a career, and shifting the representation of gender in image search results can shift people's perceptions about real-world distributions. We also discuss tensions between desires for high-quality results and broader societal goals for equality of representation in this space.