Searching for equity: White normativity in online skin cancer images

Ashley C. Rondini, Genab Diallo, Foster Bryant and Rachel H. Kowalsky

Social Science & Medicine, 2025, vol. 364, issue C

Abstract: In this paper, we examine the range of skin tones represented in publicly available online image search results through which non-medical audiences might seek information about skin cancer signs, symptoms, and risks. We use the Fitzpatrick scale, a numerical classification system grouping six human skin tones (or “phototypes”) in dermatology, as a guide for analyzing the skin tones appearing in (n = 1600) Google image search results for search terms related to skin cancer. We find that light skin tones (1,2, and 3 on the Fitzpatrick scale) comprise the significant majority (roughly 96%) of those depicted in Google image searches of information about skin cancer signs and prevention; dark skin tones (4, 5, and 6 on the Fitzpatrick scale) appear with significantly less frequency (roughly 4%) in the same search results. Disparate representation of diverse skin tones—and, more specifically, omission of dark skin images—suggests that racial biases inflect the search results generated by seemingly race-neutral skin-cancer related search terms. This embedded racial bias privileges white normativity to the disadvantage of dark-skinned patients, who are most likely to be racially classified as Black.

Date: 2025
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DOI: 10.1016/j.socscimed.2024.117523

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