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An Image of Society: Gender and Racial Representation and Impact in Image Search Results for Occupations

Published: 22 April 2021 Publication History

Abstract

Algorithmically-mediated content is both a product and producer of dominant social narratives, and it has the potential to impact users' beliefs and behaviors. We present two studies on the content and impact of gender and racial representation in image search results for common occupations. In Study 1, we compare 2020 workforce gender and racial composition to that reflected in image search. We find evidence of underrepresentation on both dimensions: women are underrepresented in search at a rate of 42% women for a field with 50% women; people of color are underrepresented with 16% in search compared to an occupation with 22% people of color (the latter being proportional to the U.S. workforce). We also compare our gender representation data with that collected in 2015 by Kay et al., finding little improvement in the last half-decade. In Study 2, we study people's impressions of occupations and sense of belonging in a given field when shown search results with different proportions of women and people of color. We find that both axes of representation as well as people's own racial and gender identities impact their experience of image search results. We conclude by emphasizing the need for designers and auditors of algorithms to consider the disparate impacts of algorithmic content on users of marginalized identities.

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      cover image Proceedings of the ACM on Human-Computer Interaction
      Proceedings of the ACM on Human-Computer Interaction  Volume 5, Issue CSCW1
      CSCW
      April 2021
      5016 pages
      EISSN:2573-0142
      DOI:10.1145/3460939
      Issue’s Table of Contents
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      Publication History

      Published: 22 April 2021
      Published in PACMHCI Volume 5, Issue CSCW1

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      Author Tags

      1. algorithm audit
      2. algorithmic bias
      3. marginalized identities
      4. search media

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