cultural-bias

A computational study reveals that large language models partially homogenize distinct Indian oral traditions, with regional language prompts surprisingly reducing fidelity to authentic narratives.

The study explores whether stereotype-loaded queries about culturally marked individuals lead to more personal information leakage from RAG systems than neutral queries, finding no evidence of such amplification after statistical corrections.

Ramsey Nasser's talk addresses the English-centric nature of programming languages and introduces an Arabic-based programming language to promote inclusivity in computing education.

A study reveals that AI models are less likely to recommend nuclear strikes when reasoning in Japanese, due to cultural embeddings in the language that subtly shape moral judgment.

This paper investigates whether large language models reproduce critical acclaim versus commercial success hierarchies in film preferences, finding across 20,000 pairwise comparisons that models consistently favor critically acclaimed but commercially obscure films, with this orientation growing with model scale.

TreeProbe is the first cultural-bias benchmark for Tibetan medicine in LLMs, containing 4,719 expert-adjudicated items across 467 diseases and 10 subtasks, revealing systematic external ontology drift in current models.

Introduces CCBench, a framework for evaluating LLMs' cultural competence via health queries with personas across six cultures, finding that even top models achieve only 20-30% culturally appropriate responses.

This paper introduces CulturalNB, a dataset of Bengali cultural question-answer pairs, and evaluates nine LLMs for cross-lingual cultural bias. Findings show that English prompting increases global narrative substitution and reduces local perspectives, revealing that cultural failures in LLMs are grounding and prioritization issues, not just missing knowledge.

Empirical study showing frontier LLMs encode a culturally skewed baseline that privileges Western viewpoints when describing and judging global streetscapes, with non-Western prompts systematically deviating more from the default.