{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T12:46:58Z","timestamp":1770814018272,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T00:00:00Z","timestamp":1770681600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Vision"],"abstract":"<jats:p>Purpose: To evaluate demographic representation in AI-generated and search-engine-sourced images of North American ophthalmologists, overall and stratified by subspecialty, and compare these with actual demographic data. Methods: This cross-sectional analysis examined 2000 images (1000 AI-generated and 1000 search-engine-sourced) across ten North American ophthalmology subspecialties. Images were sourced from four AI platforms (DALL\u00b7E 3, Firefly, Midjourney, Grok-2) and four search engines (Google, Bing, DuckDuckGo, Yahoo!). Using a standardized framework, reviewers assessed gender, race, age group, and professional attire. Pearson chi-squared tests were used to compare image sets with actual demographic data from the Association of American Medical Colleges and Canadian Institute for Health Information. Results: AI-generated images depicted 69% men compared to 64% in search-engine-sourced images (p = 0.047), though both were lower than the actual proportion of male ophthalmologists in North America (71\u201373%, p &lt; 0.001). White individuals were overrepresented in AI-generated images (81%) relative to both search-engine-sourced images (74%, p = 0.001) and actual demographic data (69%, p &lt; 0.001). Younger individuals (under 50 years) were significantly overrepresented in both image sets, with 82% in AI-generated images and 73% in search-engine-sourced images, compared to only 45\u201346% in actual demographic data (p &lt; 0.001 for both). AI-generated images also depicted ophthalmologists with significantly more stereotypical medical accessories, including stethoscopes (17% vs. 2%, p &lt; 0.001), glasses (45% vs. 30%, p &lt; 0.001), and white coats (68% vs. 53%, p &lt; 0.001), compared to search-engine-sourced images. Conclusions: AI-generated images diverge from actual demographics, presenting a younger, more stereotypical workforce that paradoxically aligns closer to gender parity than reality.<\/jats:p>","DOI":"10.3390\/vision10010010","type":"journal-article","created":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T11:16:38Z","timestamp":1770722198000},"page":"10","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Demographic Disparities in AI-Generated Versus Search-Engine-Sourced Images of Ophthalmologists: A Cross-Sectional Analysis"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-4839-5182","authenticated-orcid":false,"given":"Siddharth","family":"Gandhi","sequence":"first","affiliation":[{"name":"Faculty of Medicine, Queen\u2019s University, Kingston, ON K7L 3L4, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katherine","family":"Jung","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5948-0331","authenticated-orcid":false,"given":"Michael","family":"Balas","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, ON M5T 3A9, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Parnian","family":"Arjmand","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, ON M5T 3A9, Canada"},{"name":"School of Medicine, Toronto Metropolitan University, Toronto, ON L6T 2T9, Canada"},{"name":"Mississauga Retina Institute, Mississauga, ON L4X 2Z9, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1186\/s13012-024-01357-9","article-title":"Generative AI in Healthcare: An Implementation Science Informed Translational Path on Application, Integration and Governance","volume":"19","author":"Reddy","year":"2024","journal-title":"Implement. 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