{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T04:32:01Z","timestamp":1784003521089,"version":"3.55.0"},"reference-count":60,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Big Data &amp; Society"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:p>Previous discussions have highlighted the need for generative AI tools to become more culturally sensitive, yet often neglect the complexities of handling content about marginalized groups, who are perceived differently across cultures and religions. Our study examined the responses of two generative AI systems to homophobic statements and explored how their outputs varied when different societal and religious context information about the user was provided. Findings showed that ChatGPT 3.5's replies frequently reflected cultural relativism, as evidenced by an emphasis in the outputs on the idea that different cultures hold distinct perspectives and that these diverse viewpoints should be respected. In contrast, Bard's responses often stressed human rights and provided more support for gay people and lesbian, gay, bisexual, trans, and queer (LGBTQ)+\u2009issues. Both systems demonstrated significant variation in their responses depending on the contextual information provided in the prompts, suggesting that AI systems may adjust the degree and form of support they express for LGBTQ+\u2009people and issues according to the information they receive about a user's background. While our analysis focused specifically on chatbot responses to homophobic statements, the study underscores a broader dilemma concerning the tension between cultural relativism and universal human rights in generative AI\u2014an issue that extends beyond homophobia to include animosity toward other marginalized groups that are perceived differently across societies and religions. The study contributes to understanding the social and ethical implications of AI responses and argues that any work to make generative AI outputs more culturally diverse requires grounding in fundamental human rights.<\/jats:p>","DOI":"10.1177\/20539517251396069","type":"journal-article","created":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T17:13:41Z","timestamp":1764954821000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Cross-cultural challenges in generative AI: Addressing homophobia in diverse sociocultural contexts"],"prefix":"10.1177","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6034-7503","authenticated-orcid":false,"given":"Lilla","family":"Vicsek","sequence":"first","affiliation":[{"name":"Corvinus University of Budapest"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7804-4618","authenticated-orcid":false,"given":"Mike","family":"Zajko","sequence":"additional","affiliation":[{"name":"University of British Columbia Okanagan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7783-6963","authenticated-orcid":false,"given":"Anna","family":"Vancs\u00f3","sequence":"additional","affiliation":[{"name":"Institute of Sociology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7509-0739","authenticated-orcid":false,"given":"Judit","family":"Takacs","sequence":"additional","affiliation":[{"name":"ELTE Centre for Social Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8383-0381","authenticated-orcid":false,"given":"Szabolcs","family":"Annus","sequence":"additional","affiliation":[{"name":"E\u00f6tv\u00f6s Lor\u00e1nd University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,12,5]]},"reference":[{"key":"e_1_3_4_2_1","doi-asserted-by":"publisher","DOI":"10.1177\/2053951720949566"},{"key":"e_1_3_4_3_1","article-title":"Large language models are often politically extreme, usually ideologically inconsistent, and persuasive even in informational contexts","author":"Aldahoul N","year":"2025","unstructured":"Aldahoul N, Ibrahim H, Varvello M, et al. (2025) Large language models are often politically extreme, usually ideologically inconsistent, and persuasive even in informational contexts. arXiv preprint. arXiv:2505.04171.","journal-title":"arXiv preprint. arXiv:2505.04171"},{"key":"e_1_3_4_4_1","article-title":"Circuit tracing: revealing computational graphs in language models","author":"Ameisen E","year":"2025","unstructured":"Ameisen E, Lindsey J, Pearce A, et al. (2025) Circuit tracing: revealing computational graphs in language models. Anthropic. https:\/\/transformer-circuits.pub\/2025\/attribution-graphs\/methods.html (accessed 15 May 2025).","journal-title":"Anthropic"},{"key":"e_1_3_4_5_1","article-title":"Probing pre-trained language models for cross-cultural differences in values","author":"Arora A","year":"2022","unstructured":"Arora A, Kaffee LA, Augenstein I (2022) Probing pre-trained language models for cross-cultural differences in values. arXiv:2203.13722.","journal-title":"arXiv:2203.13722"},{"key":"e_1_3_4_6_1","unstructured":"Axios House at Davos #WEF24 (2024) Axios\u2019 Ina Fried in conversation with Open AI's Sam Altman. Youtube. Available at: https:\/\/www.youtube.com\/watch?v=QFXp_TU-bO8 (accessed 18 June 2024)."},{"key":"e_1_3_4_7_1","doi-asserted-by":"publisher","DOI":"10.1177\/0010414016666836"},{"key":"e_1_3_4_8_1","doi-asserted-by":"publisher","DOI":"10.1177\/20539517231205476"},{"key":"e_1_3_4_9_1","doi-asserted-by":"publisher","DOI":"10.1177\/2053951716652159"},{"key":"e_1_3_4_10_1","doi-asserted-by":"publisher","DOI":"10.2196\/52091"},{"key":"e_1_3_4_11_1","doi-asserted-by":"publisher","DOI":"10.1191\/1478088706qp063oa"},{"key":"e_1_3_4_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10676-024-09779-1"},{"key":"e_1_3_4_13_1","article-title":"Assessing cross-cultural alignment between ChatGPT and human societies: An empirical study","author":"Cao Y","year":"2023","unstructured":"Cao Y, Zhou L, Lee S, et al. (2023) Assessing cross-cultural alignment between ChatGPT and human societies: An empirical study. arXiv:2303.17466.","journal-title":"arXiv:2303.17466"},{"key":"e_1_3_4_14_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-51969-w"},{"key":"e_1_3_4_15_1","unstructured":"Council of Europe (2024) Council of Europe Framework Convention on Artificial Intelligence and Human Rights Democracy and the Rule of Law. https:\/\/rm.coe.int\/1680afae3c."},{"key":"e_1_3_4_16_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0133538"},{"key":"e_1_3_4_17_1","doi-asserted-by":"publisher","DOI":"10.1353\/hrq.2007.0016"},{"key":"e_1_3_4_18_1","doi-asserted-by":"publisher","DOI":"10.7591\/9780801467493"},{"key":"e_1_3_4_19_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1468-2885.2004.tb00313.x"},{"key":"e_1_3_4_20_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1468-2885.2004.tb00313.x"},{"key":"e_1_3_4_21_1","article-title":"WinoQueer: A community-in-the-loop benchmark for anti-LGBTQ+ bias in large language models","author":"Felkner VK","year":"2023","unstructured":"Felkner VK, Chang Ho-Chung H, Jang E, et al. (2023) WinoQueer: A community-in-the-loop benchmark for anti-LGBTQ+ bias in large language models. arXiv:2306.15087.","journal-title":"arXiv:2306.15087"},{"key":"e_1_3_4_22_1","doi-asserted-by":"crossref","unstructured":"Fleisig E Amsutz A Atalla C et al. (2023) Fair-Prism: Evaluating fairness-related harms in text generation. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics. July 9-14 2023. Volume 1: Long Papers. 6231\u20136251.","DOI":"10.18653\/v1\/2023.acl-long.343"},{"key":"e_1_3_4_23_1","article-title":"Who are we talking to when we talk to these bots?","author":"Fraser C","unstructured":"Fraser C (2023, December 8) Who are we talking to when we talk to these bots? Medium. Available at: https:\/\/medium.com\/@colin.fraser\/who-are-we-talking-to-when-we-talk-to-these-bots-9a7e673f8525 (accessed 18 June 2024).","journal-title":"Medium"},{"key":"e_1_3_4_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3600211.3604672"},{"key":"e_1_3_4_25_1","doi-asserted-by":"publisher","DOI":"10.1177\/20539517241252131"},{"key":"e_1_3_4_26_1","doi-asserted-by":"publisher","DOI":"10.1093\/he\/9780199644704.001.0001"},{"key":"e_1_3_4_27_1","article-title":"Can (A)I change your mind? Comparing the persuasive power of humans and large language models","author":"Havin M","year":"2025","unstructured":"Havin M, Wharton Kleinman T, Koren M, et al. (2025) Can (A)I change your mind? Comparing the persuasive power of humans and large language models. arXiv:2503.01844v3.","journal-title":"arXiv:2503.01844v3"},{"key":"e_1_3_4_28_1","doi-asserted-by":"publisher","DOI":"10.1177\/1461444820958725"},{"key":"e_1_3_4_29_1","article-title":"Misgendered: Limits of large language models in understanding pronouns","author":"Hossain T","year":"2023","unstructured":"Hossain T, Dev S, Singh S (2023) Misgendered: Limits of large language models in understanding pronouns. arXiv:2306.03950.","journal-title":"arXiv:2306.03950"},{"key":"e_1_3_4_30_1","doi-asserted-by":"publisher","DOI":"10.1111\/lnc3.12432"},{"issue":"1","key":"e_1_3_4_31_1","first-page":"1","article-title":"We are the AI problem","volume":"74","author":"Jacobi T","year":"2024","unstructured":"Jacobi T, Sag M (2024) We are the AI problem. Emory Law Journal Online 74(1): 1\u201318. Available at SSRN: https:\/\/ssrn.com\/abstract=4820165 (accessed 30 June 2024).","journal-title":"Emory Law Journal Online"},{"key":"e_1_3_4_32_1","doi-asserted-by":"publisher","DOI":"10.1080\/13642987.2017.1290930"},{"key":"e_1_3_4_33_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.queerinai-main.3"},{"key":"e_1_3_4_34_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1536-7150.2007.00502.x"},{"key":"e_1_3_4_35_1","article-title":"The colorful future of LLMs: Evaluating and improving LLMs as emotional supporters for queer youth","author":"Lissak S","year":"2024","unstructured":"Lissak S, Calderon N, Shenkman G, et al. (2024) The colorful future of LLMs: Evaluating and improving LLMs as emotional supporters for queer youth. arXiv:2402.11886.","journal-title":"arXiv:2402.11886"},{"key":"e_1_3_4_36_1","article-title":"Ethics and society newsletter #4: bias in text-to-image models","author":"Luccioni S","unstructured":"Luccioni S, Pistilli G, Rajani N, et al. (2023, June 26) Ethics and society newsletter #4: bias in text-to-image models. Hugging Face. Available at: https:\/\/huggingface.co\/blog\/ethics-soc-4 (accessed 18 June 2024).","journal-title":"Hugging Face"},{"key":"e_1_3_4_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clsr.2018.05.017"},{"key":"e_1_3_4_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3593013.3594109"},{"key":"e_1_3_4_39_1","doi-asserted-by":"publisher","DOI":"10.18574\/nyu\/9781479833641.001.0001"},{"key":"e_1_3_4_40_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.ltedi-1.4"},{"key":"e_1_3_4_41_1","unstructured":"OpenAI (2025) Introducing OpenAI for Countries. https:\/\/openai.com\/global-affairs\/openai-for-countries\/ (accessed 15 May 2025)."},{"key":"e_1_3_4_42_1","doi-asserted-by":"publisher","DOI":"10.1093\/law\/9780192882486.003.0035"},{"key":"e_1_3_4_43_1","article-title":"A human rights-based approach to responsible AI (No. arXiv:2210.02667)","author":"Prabhakaran V","year":"2022","unstructured":"Prabhakaran V, Mitchell M, Gebru T, et al. (2022) A human rights-based approach to responsible AI (No. arXiv:2210.02667). arXiv.","journal-title":"arXiv"},{"key":"e_1_3_4_44_1","doi-asserted-by":"publisher","DOI":"10.1093\/hcr\/hqad050"},{"key":"e_1_3_4_45_1","article-title":"The political preferences of LLMs","author":"Rozado D","year":"2024","unstructured":"Rozado D (2024) The political preferences of LLMs. arXiv:2402.01789.","journal-title":"arXiv:2402.01789"},{"key":"e_1_3_4_46_1","unstructured":"Schwartz O (2019 November 25) In 2016 Microsoft\u2019s Racist Chatbot Revealed the Dangers of Online Conversation. IEEE Spectrum. Available at: https:\/\/spectrum.ieee.org\/in-2016-microsofts-racist-chatbot-revealed-the-dangers-of-online-conversation (accessed 18 June 2024)."},{"key":"e_1_3_4_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3600211.3604673"},{"key":"e_1_3_4_48_1","article-title":"Beyond memorization: Violating privacy via inference with large language models","author":"Staab R","year":"2023","unstructured":"Staab R, Vero M, Balunovi\u0107 M, et al. (2023) Beyond memorization: Violating privacy via inference with large language models. arXiv preprint arXiv:2310.07298.","journal-title":"arXiv preprint arXiv:2310.07298"},{"issue":"1","key":"e_1_3_4_49_1","first-page":"66","article-title":"Human rights as a factor in the AI alignment","volume":"4","author":"Strz\u0119pek K","year":"2024","unstructured":"Strz\u0119pek K (2024) Human rights as a factor in the AI alignment. GIS Odyssey Journal 4(1): 66\u201377.","journal-title":"GIS Odyssey Journal"},{"key":"e_1_3_4_50_1","doi-asserted-by":"publisher","DOI":"10.1177\/20539517231219241"},{"key":"e_1_3_4_51_1","doi-asserted-by":"publisher","DOI":"10.1080\/0966369X.2018.1563523"},{"key":"e_1_3_4_52_1","article-title":"Auditing and mitigating cultural bias in LLMs","author":"Tao Y","year":"2023","unstructured":"Tao Y, Viberg O, Baker R, et al. (2023) Auditing and mitigating cultural bias in LLMs. ArXiv: abs\/2311.14096.","journal-title":"ArXiv"},{"key":"e_1_3_4_53_1","doi-asserted-by":"publisher","DOI":"10.1007\/s43681-024-00547-x"},{"key":"e_1_3_4_54_1","unstructured":"Tiku N Oremus W (2023 March 1) The right\u2019s new culture-war target: \u2018Woke AI.\u2019 Washington Post. Available at: https:\/\/www.washingtonpost.com\/technology\/2023\/02\/24\/woke-ai-chatgpt-culture-war\/ (accessed 18 June 2024)."},{"key":"e_1_3_4_55_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.queerinai-main.2"},{"key":"e_1_3_4_56_1","doi-asserted-by":"publisher","DOI":"10.1177\/08944393231152946"},{"key":"e_1_3_4_57_1","article-title":"Sociotechnical safety evaluation of generative AI systems","author":"Weidinger L","year":"2023","unstructured":"Weidinger L, Rauh M, Marchal N, et al. (2023) Sociotechnical safety evaluation of generative AI systems. arXiv:2310.11986.","journal-title":"arXiv:2310.11986"},{"key":"e_1_3_4_58_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11199-018-0989-2"},{"key":"e_1_3_4_59_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00146-021-01153-9"},{"key":"e_1_3_4_60_1","doi-asserted-by":"publisher","DOI":"10.1111\/socf.12507"},{"key":"e_1_3_4_61_1","article-title":"GPTBIAS: A comprehensive framework for evaluating bias in large language models","author":"Zhao J","year":"2023","unstructured":"Zhao J, Fang M, Pan S, et al. (2023) GPTBIAS: A comprehensive framework for evaluating bias in large language models. arXiv:2312.06315.","journal-title":"arXiv:2312.06315"}],"container-title":["Big Data &amp; Society"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/20539517251396069","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/20539517251396069","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/20539517251396069","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T13:01:33Z","timestamp":1777381293000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/20539517251396069"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":60,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["10.1177\/20539517251396069"],"URL":"https:\/\/doi.org\/10.1177\/20539517251396069","relation":{},"ISSN":["2053-9517","2053-9517"],"issn-type":[{"value":"2053-9517","type":"print"},{"value":"2053-9517","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12]]},"article-number":"20539517251396069"}}