Conceptualizing and Assessing Cross-Cultural Bias in LLMs
Published:Dec 26, 2025 00:27
•1 min read
•ArXiv
Analysis
This paper addresses a critical issue: the potential for cultural bias in large language models (LLMs) and the need for robust assessment of their societal impact. It highlights the limitations of current evaluation methods, particularly the lack of engagement with real-world users. The paper's focus on concrete conceptualization and effective evaluation of harms is crucial for responsible AI development.
Key Takeaways
- •LLMs exhibit cross-cultural bias and require careful evaluation.
- •Current evaluation methods may lack real-world user engagement.
- •The paper aims to provide a framework for conceptualizing and assessing the societal impact of bias.
- •The research is inspired by prior work on cultural bias in NLP.
Reference
“Researchers may choose not to engage with stakeholders actually using that technology in real life, which evades the very fundamental problem they set out to address.”