Perceptions in pixels: analyzing perceived gender and skin tone in real-world image search results
Keywords: image search, gender, skin tone, information retreival
Abstract: The results returned by image search engines have the power to shape peoples' perceptions about social groups. Existing work on image search engines leverages hand-selected queries for occupations like "doctor" and "engineer" to quantify racial and gender bias in search results. We complement this work by analyzing peoples' real-world image search queries and measuring the distributions of perceived gender, skin tone, and age in their results. Specifically, we utilize 54,070 unique image search queries from a representative sample of 643 US residents. For each of these queries we collect the top 50 results returned on both Google and Bing Images.
We learn multiple new things from analysis of real-world image search queries. First, less than 5% of unique queries are open-ended people queries (i.e., not queries for named entities). Second, fashion search is by far the most common category of open-ended people queries, accounting for over 30% of the total. Third, the modal skin tone on the Monk Skin Tone scale is two out of ten (the second lightest) for images from both search engines. Finally, we observe a bias against older people: eleven of our top fifteen query categories have a median age that is lower than the median age in the US.
Track: Responsible Web
Submission Guidelines Scope: Yes
Submission Guidelines Blind: Yes
Submission Guidelines Format: Yes
Submission Guidelines Limit: Yes
Submission Guidelines Authorship: Yes
Student Author: Yes
Submission Number: 2112
Loading