{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T16:59:29Z","timestamp":1773680369180,"version":"3.50.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T00:00:00Z","timestamp":1773619200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T00:00:00Z","timestamp":1773619200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Universidade Estadual Paulista J\u00falio De Mesquita Filho"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["AI Ethics"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1007\/s43681-026-01066-7","type":"journal-article","created":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T16:15:01Z","timestamp":1773677701000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Bias beyond borders: quantifying gender and ethnic stereotypes across countries in AI image generation"],"prefix":"10.1007","volume":"6","author":[{"given":"Giovanni","family":"Franco","sequence":"first","affiliation":[]},{"given":"Regilene Aparecida","family":"Sarzi-Ribeiro","sequence":"additional","affiliation":[]},{"given":"Jo\u00e3o Paulo","family":"Papa","sequence":"additional","affiliation":[]},{"given":"Kelton Augusto Pontara","family":"da Costa","sequence":"additional","affiliation":[]},{"given":"Felipe","family":"Mahlow","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,3,16]]},"reference":[{"key":"1066_CR1","unstructured":"Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., Chen, M.: Hierarchical Text-Conditional Image Generation with CLIP Latents (2022). arXiv: 2204.06125"},{"key":"1066_CR2","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-Resolution Image Synthesis with Latent Diffusion Models (2022). arXiv: 2112.10752","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"1066_CR3","unstructured":"Podell, D., English, Z., Lacey, K., Blattmann, A., Dockhorn, T., M\u00fcller, J., Penna, J., Rombach, R.: SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis (2023). arXiv: 2307.01952"},{"key":"1066_CR4","unstructured":"Team, G., Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A.M., Hauth, A., Millican, K., et al.: Gemini: a family of highly capable multimodal models. arXiv:2312.11805 (2023)"},{"key":"1066_CR5","unstructured":"Labs, B.F., Batifol, S., Blattmann, A., Boesel, F., Consul, S., Diagne, C., Dockhorn, T., English, J., English, Z., Esser, P., Kulal, S., Lacey, K., Levi, Y., Li, C., Lorenz, D., M\u00fcller, J., Podell, D., Rombach, R., Saini, H., Sauer, A., Smith, L.: FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space (2025). arXiv: 2506.15742"},{"key":"1066_CR6","unstructured":"Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., Sutskever, I.: Zero-Shot Text-to-Image Generation (2021). arXiv: 2102.12092"},{"key":"1066_CR7","unstructured":"Luccioni, A.S., Akiki, C., Mitchell, M., Jernite, Y.: Stable Bias: Analyzing Societal Representations in Diffusion Models (2023). arXiv: 2303.11408"},{"key":"1066_CR8","doi-asserted-by":"crossref","unstructured":"Crawford, K.: The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press, ??? (2021)","DOI":"10.12987\/9780300252392"},{"issue":"1","key":"1066_CR9","doi-asserted-by":"publisher","first-page":"262","DOI":"10.5753\/jbcs.2025.4166","volume":"31","author":"WA Cruz-Casta\u00f1eda","year":"2025","unstructured":"Cruz-Casta\u00f1eda, W.A., Amadeus, M., Zanella, A.F., Mahlow, F.R.P.: From pampas to pixels: fine-tuning diffusion models for ga\u00facho heritage. J. Braz. Comput. Soc. 31(1), 262\u2013270 (2025)","journal-title":"J. Braz. Comput. Soc."},{"key":"1066_CR10","unstructured":"Birhane, A., Prabhu, V.U., Kahembwe, E.: Multimodal datasets: misogyny, pornography, and malignant stereotypes (2021). arXiv: 2110.01963"},{"issue":"2","key":"1066_CR11","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1007\/s00146-023-01780-4","volume":"40","author":"O Bendel","year":"2025","unstructured":"Bendel, O.: Image synthesis from an ethical perspective. AI & SOCIETY 40(2), 437\u2013446 (2025)","journal-title":"AI & SOCIETY"},{"key":"1066_CR12","unstructured":"Zhou, M., Abhishek, V., Derdenger, T., Kim, J., Srinivasan, K.: Bias in generative ai. arXiv:2403.02726 (2024)"},{"issue":"12","key":"1066_CR13","doi-asserted-by":"publisher","first-page":"1000","DOI":"10.1109\/TLA.2024.10789626","volume":"22","author":"FRP Mahlow","year":"2024","unstructured":"Mahlow, F.R.P., Zanella, A.F., Casta\u00f1eda, W.A.C., Sarzi-Ribeiro, R.A.: Illustrating classic brazilian books using a text-to-image diffusion model. IEEE Lat. Am. Trans. 22(12), 1000\u20131008 (2024)","journal-title":"IEEE Lat. Am. Trans."},{"key":"1066_CR14","doi-asserted-by":"crossref","unstructured":"Wang, W., Bai, H., Huang, J.-T., Wan, Y., Yuan, Y., Qiu, H., Peng, N., Lyu, M.: New job, new gender? measuring the social bias in image generation models. In: Proceedings of the 32nd ACM International Conference on Multimedia, pp. 3781\u20133789 (2024)","DOI":"10.1145\/3664647.3681433"},{"issue":"4","key":"1066_CR15","doi-asserted-by":"publisher","first-page":"2229","DOI":"10.1007\/s00146-024-02129-1","volume":"40","author":"LG Locke","year":"2025","unstructured":"Locke, L.G., Hodgdon, G.: Gender bias in visual generative artificial intelligence systems and the socialization of ai. AI & SOCIETY 40(4), 2229\u20132236 (2025)","journal-title":"AI & SOCIETY"},{"key":"1066_CR16","unstructured":"Girrbach, L., Alaniz, S., Smith, G., Akata, Z.: A Large Scale Analysis of Gender Biases in Text-to-Image Generative Models (2025). arXiv: 2503.23398"},{"issue":"2","key":"1066_CR17","doi-asserted-by":"publisher","first-page":"35","DOI":"10.3390\/jimaging11020035","volume":"11","author":"Y Wu","year":"2025","unstructured":"Wu, Y., Nakashima, Y., Garcia, N.: Revealing gender bias from prompt to image in stable diffusion. J. Imaging 11(2), 35 (2025)","journal-title":"J. Imaging"},{"key":"1066_CR18","doi-asserted-by":"crossref","unstructured":"D\u2019Inc\u00e0, M., Peruzzo, E., Mancini, M., Xu, D., Goel, V., Xu, X., Wang, Z., Shi, H., Sebe, N.: OpenBias: Open-set Bias Detection in Text-to-Image Generative Models (2024). arXiv: 2404.07990","DOI":"10.1109\/CVPR52733.2024.01162"},{"key":"1066_CR19","unstructured":"Vice, J., Akhtar, N., Hartley, R., Mian, A.: Exploring Bias in over 100 Text-to-Image Generative Models (2025). arXiv: 2503.08012"},{"key":"1066_CR20","doi-asserted-by":"crossref","unstructured":"Sufian, A., Distante, C., Leo, M., Salam, H.: T2IBias: Uncovering Societal Bias Encoded in the Latent Space of Text-to-Image Generative Models (2025). arXiv: 2511.10089","DOI":"10.1007\/978-3-032-16886-3_4"},{"key":"1066_CR21","doi-asserted-by":"crossref","unstructured":"Nadeem, M., Sohail, S.S., Cambria, E., Schuller, B.W., Hussain, A.: Gender Bias in Text-to-Video Generation Models: A case study of Sora (2025). arXiv: 2501.01987","DOI":"10.1109\/MIS.2025.3561475"},{"key":"1066_CR22","doi-asserted-by":"crossref","unstructured":"Nakamura, Y., Sato, K., Suzuki, A., Tanaka, H.: Cross-modal bias transfer in aligned video diffusion models. Preprints (2026) 10.20944\/preprints202601.1956.v1","DOI":"10.20944\/preprints202601.1956.v1"},{"key":"1066_CR23","unstructured":"Hall, M., Ross, C., Williams, A., Carion, N., Drozdzal, M., Soriano, A.R.: DIG. In: Evaluating Disparities in Image Generations with Indicators for Geographic Diversity (2024). arXiv: 2308.06198"},{"key":"1066_CR24","unstructured":"Sureddy, A., Padalia, D., Periyakaruppa, N., Saha, O., Williams, A., Romero-Soriano, A., Richards, M., Kirichenko, P., Hall, M.: Decomposed evaluations of geographic disparities in text-to-image models (2024). arXiv: 2406.11988"},{"key":"1066_CR25","doi-asserted-by":"crossref","unstructured":"Basu, A., Babu, R.V., Pruthi, D.: Inspecting the Geographical Representativeness of Images from Text-to-Image Models (2023). arXiv: 2305.11080","DOI":"10.1109\/ICCV51070.2023.00474"},{"key":"1066_CR26","doi-asserted-by":"crossref","unstructured":"Friedrich, F., H\u00e4mmerl, K., Schramowski, P., Brack, M., Libovicky, J., Kersting, K., Fraser, A.: Multilingual Text-to-Image Generation Magnifies Gender Stereotypes and Prompt Engineering May Not Help You (2025). arXiv: 2401.16092","DOI":"10.18653\/v1\/2025.acl-long.966"},{"key":"1066_CR27","doi-asserted-by":"crossref","unstructured":"Wolfe, R., Caliskan, A.: American == White in Multimodal Language-and-Image AI (2022). arXiv: 2207.00691","DOI":"10.1145\/3514094.3534136"},{"key":"1066_CR28","unstructured":"Seo, H., Choi, S., Hong, M., Zhou, Y., Kim, J., Ismaila, L., Etori, N., Agarwal, M., Liu, Z., Kim, J., Oh, J.: Exposing Blindspots: Cultural Bias Evaluation in Generative Image Models (2025). arXiv: 2510.20042"},{"key":"1066_CR29","unstructured":"Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., Krueger, G., Sutskever, I.: Learning Transferable Visual Models From Natural Language Supervision (2021). arXiv: 2103.00020"},{"key":"1066_CR30","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"7825","key":"1066_CR31","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1038\/s41586-020-2649-2","volume":"585","author":"CR Harris","year":"2020","unstructured":"Harris, C.R., Millman, K.J., Walt, S.J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N.J., Kern, R., Picus, M., Hoyer, S., Kerkwijk, M.H., Brett, M., Haldane, A., R\u00edo, J.F., Wiebe, M., Peterson, P., G\u00e9rard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C., Oliphant, T.E.: Array programming with NumPy. Nature 585(7825), 357\u2013362 (2020). https:\/\/doi.org\/10.1038\/s41586-020-2649-2","journal-title":"Nature"},{"key":"1066_CR32","doi-asserted-by":"crossref","unstructured":"Fix, E., Hodges, J.L.: Discriminatory analysis. nonparametric discrimination: Consistency properties. International Statistical Review \/ Revue Internationale de Statistique 57(3), 238\u2013247 (1989). Accessed 2025\u201311-26","DOI":"10.2307\/1403797"},{"key":"1066_CR33","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, E.: Scikit-learn: Machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"1066_CR34","unstructured":"Yang, A., Li, A., Yang, B., Zhang, B., Hui, B., Zheng, B., Yu, B., Gao, C., Huang, C., Lv, C., Zheng, C., Liu, D., Zhou, F., Huang, F., Hu, F., Ge, H., Wei, H., Lin, H., Tang, J., Yang, J., Tu, J., Zhang, J., Yang, J., Yang, J., Zhou, J., Zhou, J., Lin, J., Dang, K., Bao, K., Yang, K., Yu, L., Deng, L., Li, M., Xue, M., Li, M., Zhang, P., Wang, P., Zhu, Q., Men, R., Gao, R., Liu, S., Luo, S., Li, T., Tang, T., Yin, W., Ren, X., Wang, X., Zhang, X., Ren, X., Fan, Y., Su, Y., Zhang, Y., Zhang, Y., Wan, Y., Liu, Y., Wang, Z., Cui, Z., Zhang, Z., Zhou, Z., Qiu, Z.: Qwen3 Technical Report (2025). arXiv: 2505.09388"},{"key":"1066_CR35","doi-asserted-by":"crossref","unstructured":"Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning representations by back-propagating errors. nature 323(6088), 533\u2013536 (1986)","DOI":"10.1038\/323533a0"},{"key":"1066_CR36","unstructured":"Maaten, L., Hinton, G.: Visualizing data using t-sne. Journal of machine learning research 9(11) (2008)"},{"key":"1066_CR37","doi-asserted-by":"crossref","unstructured":"McInnes, L., Healy, J., Melville, J.: Umap: Uniform manifold approximation and projection for dimension reduction. arXiv:1802.03426 (2018)","DOI":"10.21105\/joss.00861"},{"key":"1066_CR38","unstructured":"U.S. Census Bureau: (2020) Census: Key Statistics on Race, Hispanic Origin, and the Population of the United States. https:\/\/www.census.gov\/library\/publications\/2021\/dec\/2020-census-key-statistics.html (2021)"},{"key":"1066_CR39","unstructured":"(IBGE), I.: Censo Demogr\u00e1fico (2022): Resultados de Cor ou Ra\u00e7a - Caracter\u00edsticas Gerais da Popula\u00e7\u00e3o. https:\/\/www.ibge.gov.br\/estatisticas\/sociais\/populacao\/22827-censo-demografico-2022.html (2022)"},{"key":"1066_CR40","unstructured":"(INDEC), I.: Censo Nacional de Poblaci\u00f3n, Hogares y Viviendas 2022 (CNPHV 2022): Resultados Definitivos sobre Autoidentificaci\u00f3n \u00c9tnica. https:\/\/www.indec.gob.ar\/indec\/web\/Nivel3-Tema-2-41 (2022)"},{"key":"1066_CR41","unstructured":"(INE), I.: Radiograf\u00eda de G\u00e9nero: Pueblos Originarios en Chile 2017. https:\/\/www.ine.gob.cl\/docs\/default-source\/genero\/documentos-de-an%C3%A1lisis\/documentos\/radiografia-de-genero-pueblos-originarios-chile2017.pdf (2017)"},{"key":"1066_CR42","unstructured":"(DANE), D.: Censo Nacional de Poblaci\u00f3n y Vivienda 2018 (CNPV 2018): Resultados de Autorreconocimiento \u00c9tnico. https:\/\/www.dane.gov.co\/index.php\/estadisticas-por-tema\/enfoque-diferencial-e-interseccional\/autorreconocimiento-etnico (2018)"},{"key":"1066_CR43","unstructured":"(INE), I.: Censo Nacional de Poblaci\u00f3n y Vivienda 2011: Resultados sobre Autoidentificaci\u00f3n \u00c9tnica. https:\/\/saludindigena.files.wordpress.com\/2013\/10\/primerosresultadosindigena2011.pdf (2011)"},{"key":"1066_CR44","doi-asserted-by":"publisher","unstructured":"Guzm\u00e1n, M.G.R., Blanco, T.N.: Self-rated health and sociodemographic inequalities among venezuelan adults: a study based on the national survey of living conditions (encovi 2021). Cad. Saude Publica 40(6), 00149323 (2024). https:\/\/doi.org\/10.1590\/0102-311XEN149323. Notes the use of 2011 census weights as the necessary standard for population calibration in the absence of more recent granular data","DOI":"10.1590\/0102-311XEN149323"},{"key":"1066_CR45","doi-asserted-by":"publisher","unstructured":"Villamizar-Chaparro, M.: The demography of crisis-driven outflows from venezuela. Popul. Dev. Rev. 50(2), 321\u2013345 (2024). https:\/\/doi.org\/10.1111\/padr.12613. Discusses demographic adjustments using the 2011 census as the last complete baseline due to the limited accessibility of subsequent official data","DOI":"10.1111\/padr.12613"},{"key":"1066_CR46","unstructured":"(StatCan), S.: Census Profile, (2021) Census of Population: Canada. https:\/\/www12.statcan.gc.ca\/census-recensement\/2021\/dp-pd\/prof\/details\/page.cfm?Lang=E&TABID=1&Details=1&Code1=01&Code2=1&SearchText=Canada&SearchType=Begins&SearchPR=01&B1=All (2021)"},{"key":"1066_CR47","unstructured":"(INE), I.: Censo Nacional de Poblaci\u00f3n y Vivienda 2018: Resultados de Pertenencia a Pueblo y G\u00c9nero. https:\/\/www.ine.gob.gt\/sistema\/uploads\/2021\/02\/10\/e844b36056341270f2f36087955c4d53.pdf (2018)"},{"key":"1066_CR48","unstructured":"(INEI), I.: Censo Nacional de Poblaci\u00f3n, Hogares y Vivienda 2017: Caracter\u00edsticas de la Poblaci\u00f3n. https:\/\/www.inei.gob.pe\/media\/MenuRecursivo\/publicaciones_digitales\/Est\/Lib1530\/Censo2017_Caracteristicas%20de%20la%20poblacion.pdf (2017)"},{"key":"1066_CR49","unstructured":"(INEGI), I.: Censo de Poblaci\u00f3n y Vivienda 2020: Poblaci\u00f3n Ind\u00edgena y Afrodescendiente. https:\/\/www.inegi.org.mx\/programas\/ccpv\/2020\/ (2020)"}],"container-title":["AI and Ethics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s43681-026-01066-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s43681-026-01066-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s43681-026-01066-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T16:15:18Z","timestamp":1773677718000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s43681-026-01066-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,16]]},"references-count":49,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["1066"],"URL":"https:\/\/doi.org\/10.1007\/s43681-026-01066-7","relation":{},"ISSN":["2730-5953","2730-5961"],"issn-type":[{"value":"2730-5953","type":"print"},{"value":"2730-5961","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,16]]},"assertion":[{"value":"29 January 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 February 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 March 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"The authors declare no Conflict of interest.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"203"}}