An Image of Society

Citations Over TimeTop 10% of 2021 papers

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.

Related Papers

• → The Past and Future Evolution of the Dental Workforce Team(2012)13 cited
• → Workforce Trends and Challenges(2018)4 cited
• → “Primitive race”, “pure race”, “brown race”, “every race”: Louis Freycinet’s Understanding of Human Difference in Oceania(2013)1 cited
• → Defining the Wind Energy Workforce Gap(2022)5 cited
• → The Beginning of Chunpyeong(天坪) Culture at Mt. Baekdu(白頭) and the Formation of the Korean people(Han韓 race·Yemaek濊貊 race·Saepark새밝 race·Maek貊 race) in early Baedalkook(倍達國)(2020)