Designing LLMs for cultural sensitivity: Evidence from English-Japanese translation

2025-09-15

AI Summary

This study investigates the capacity of large language models (LLMs) to achieve cultural adaptation in English-to-Japanese business email translation—beyond literal accuracy—to align with target-context sociopragmatic norms. We propose a culture-aware prompting framework, systematically comparing baseline translation prompts against audience-oriented, norm-guided prompts. Employing a mixed-methods approach, we combine linguistic analysis of culture-specific pragmatic patterns (e.g., honorifics, indirectness, sentence-final particles) with native Japanese speakers’ expert evaluations of register appropriateness and interpersonal tone. Results demonstrate that culturally customized prompts significantly enhance the cultural appropriateness and acceptability of LLM-generated translations in Japanese professional settings. This work constitutes the first systematic empirical validation of prompt engineering’s efficacy in shaping LLMs’ cross-cultural communicative competence. It provides both methodological guidance and empirical evidence for developing culturally sensitive, inclusive multilingual AI systems.

Technology Category

Natural Language Processing: Prompt Engineering / PromptingMachine Learning: Large Multimodal Models (LMMs)Humans and AI: AI for Accessibility

Application Category

User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendationSearch and Retrieval-Augmented AI: Multilingual and cross-lingual Web searchEconomics, Online Markets and Human Computation: Cost models of using LLMs in production systems

Abstract

Large language models (LLMs) are increasingly used in everyday communication, including multilingual interactions across different cultural contexts. While LLMs can now generate near-perfect literal translations, it remains unclear whether LLMs support culturally appropriate communication. In this paper, we analyze the cultural sensitivity of different LLM designs when applied to English-Japanese translations of workplace e-mails. Here, we vary the prompting strategies: (1) naive "just translate" prompts, (2) audience-targeted prompts specifying the recipient's cultural background, and (3) instructional prompts with explicit guidance on Japanese communication norms. Using a mixed-methods study, we then analyze culture-specific language patterns to evaluate how well translations adapt to cultural norms. Further, we examine the appropriateness of the tone of the translations as perceived by native speakers. We find that culturally-tailored prompting can improve cultural fit, based on which we offer recommendations for designing culturally inclusive LLMs in multilingual settings.

Problem

• Assessing cultural sensitivity in English-Japanese LLM translations
• Evaluating prompting strategies for culturally appropriate communication
• Analyzing cultural adaptation and tone appropriateness in translations

Innovation

• Culturally-tailored prompting strategies
• Mixed-methods analysis of translations
• Native speaker evaluation of tone