Examining Multimodal Gender and Content Bias in ChatGPT-4o
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Abstract (arXiv)
This study investigates ChatGPT-4o's multimodal content generation, highlighting significant disparities in its treatment of sexual content and nudity versus violent and drug-related themes. Detailed analysis reveals that ChatGPT-4o consistently censors sexual content and nudity, while showing leniency towards violence and drug use. Moreover, a pronounced gender bias emerges, with female-specific content facing stricter regulation compared to male-specific content. This disparity likely stems from media scrutiny and public backlash over past AI controversies, prompting tech companies to impose stringent guidelines on sensitive issues to protect their reputations. Our findings emphasize the urgent need for AI systems to uphold genuine ethical standards and accountability, transcending mere political correctness. This research contributes to the understanding of biases in AI-driven language and multimodal models, calling for more balanced and ethical content moderation practices.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 6 of its 36 references that are in the map. First posted on arXiv 28 Nov 2024.
Builds on
6 of 36 references.
References · 6
- 2023Jailbroken: How Does LLM Safety Training Fail?cited by 1,565
- 2023Jailbreaking Black Box Large Language Models in Twenty Queriescited by 1,326
- 2024Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attackscited by 450
- 2020The Creation and Detection of Deepfakes: A Surveycited by 246
- 2024Dialect prejudice predicts AI decisions about people's character, employability, and criminalitycited by 35
- 2023Auditing Elon Musk's Impact on Hate Speech and Botscited by 8
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Citing papers per year: 2025: 2; 2026: 1.
3 papers.