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UW CSE’s Matt Kay co-authors study on gender representation and stereotypes in online image search results

Female construction worker imagesToday, UW announced the results of a new study examining gender bias in online image search results associated with various occupations. The study, which will be presented at the Association for Computing Machinery’s CHI 2015 Conference later this month, raises interesting questions about how information systems influence behavior and whether search algorithms should be adjusted to counter occupational stereotypes when it comes to gender.

Co-authors Matt Kay (a UW CSE Ph.D. student), Cynthia Matuszek (a UW CSE Ph.D. alum and University of Maryland faculty member), and Sean Munson (a UW Human-Centered Design & Engineering faculty member) analyzed how well search results match reality when it comes to the gender ratio by comparing Google image search results to employment data for 45 occupations from the U.S. Bureau of Labor Statistics. The researchers also explored how the genders are qualitatively represented in search results, and how those results influence people’s perceptions of gender in different fields.

Read the UW press release here.

Read the paper here.

Read coverage of the study’s findings by The Atlantic, The Verge, PC World, GeekWire and Business Insider.