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    Unequal Representation and Gender Stereotypes in Image Search Results for Occupations

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    KayMatuszekMunsonCHI2015GenderImageSearch.pdf (537.6Kb)
    Links to Files
    https://dl.acm.org/citation.cfm?id=2702520
    Permanent Link
    10.1145/2702123.2702520
    http://hdl.handle.net/11603/11254
    Collections
    • UMBC Computer Science and Electrical Engineering Department
    • UMBC Faculty Collection
    Metadata
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    Author/Creator
    Kay, Matthew
    Matuszek, Cynthia
    Munson, Sean A.
    Date
    2015-04-18
    Type of Work
    10 PAGES
    Text
    conference papers and proceedings preprints
    Citation of Original Publication
    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
    Rights
    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.
    Subjects
    Representation
    bias
    stereotypes
    stereotypes
    Interactive Robotics and Language Lab
    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.


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    Albin O. Kuhn Library & Gallery
    University of Maryland, Baltimore County
    1000 Hilltop Circle
    Baltimore, MD 21250
    www.umbc.edu/scholarworks

    Contact information:
    Email: scholarworks-group@umbc.edu
    Phone: 410-455-3544


    If you wish to submit a copyright complaint or withdrawal request, please email mdsoar-help@umd.edu.