Cross-cultural challenges in generative AI: Addressing homophobia in diverse sociocultural contexts

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)+ issues. 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+ people 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—an 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.

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Publication Details

Journal
Big Data & Society
Published
2025-12-01
DOI
https://doi.org/10.1177/20539517251396069
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00

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article

Cross-cultural challenges in generative AI: Addressing homophobia in diverse sociocultural contexts

Judit Takács, Mike Zajko, Anna Vancsó, Lilla Vicsek et al.
Big Data & Society
AI in Service Interactions
article

Cross-cultural challenges in generative AI: Addressing homophobia in diverse sociocultural contexts

Judit Takács, Mike Zajko, Anna Vancsó, Lilla Vicsek, Szabolcs Annus
article en

Abstract

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)+ issues. 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+ people 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—an 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.

Big Data & SocietyVol. 12(4)
Eötvös Loránd University (HU), University of British Columbia (CA), Corvinus University of Budapest (HU), Slovak Academy of Sciences (SK), National Centre for Social research (GR), Centre for Social Sciences (HU), University of British Columbia, Okanagan Campus (CA), Okanagan University College (CA)
Budapesti Corvinus Egyetem
Openalex Percentile: Top 79%
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