职业提示揭示大型语言模型中的文化偏见
Occupational Prompting Reveals Cultural Bias in Large Language Models
AI总结：
通过职业提示（如会计师、教师）替代国籍提示，研究开源LLM在价值观调查中的响应，发现不同职业导致文化地图内偏移，表明职业角色引发结构化价值模式。
摘要：
社会角色塑造期望、优先级和判断，但大型语言模型（LLM）如何将职业身份与更广泛的文化价值模式关联仍不清楚。先前工作使用基于国籍的文化提示来研究LLM对价值观调查问题的响应如何与人类文化基准对齐。本文通过用职业提示替代文化提示，扩展了该框架，以检查职业角色线索如何影响开源LLM的价值观调查响应。使用基于综合价值观调查问题的调查评估流程，我们将模型响应投影到二维Inglehart-Welzel文化空间。我们提示开源LLM以职业身份（如会计师、教师、工程师和护士）回答问题，然后分析这些职业条件化响应在文化地图上的位置。结果表明，当用职业而非国籍身份提示开源LLM时，其响应仍位于文化地图的广泛西方倾向区域。然而，不同职业在该区域内引入偏移，产生不同的职业偏差。这表明职业提示并非被视为中性角色标签，而是引发结构化价值模式。这些发现将基于调查的文化偏见评估扩展到国籍提示之外，并提供了研究职业角色如何塑造LLM中价值表达的框架。
英文摘要：
Social roles shape expectations, priorities, and judgments, yet it remains unclear how large language models (LLMs) associate occupational identities with broader cultural value patterns. Prior work used nationality-based cultural prompting to study how LLM responses to value-survey questions align with human cultural benchmarks. In this paper, we extend that framework by replacing cultural prompting with occupational prompting to examine how professional-role cues influence value-survey responses in open-weight LLMs. Using a survey-grounded evaluation pipeline based on questions from the Integrated Values Surveys, we project model responses into the two-dimensional Inglehart--Welzel cultural space. We prompt open-weight LLMs to answer questions under occupational identities such as accountant, teacher, engineer, and nurse, and then analyze how these occupation-conditioned responses are positioned on the cultural map. Our results show that when open-weight LLMs are prompted with occupations rather than national identities, their responses remain within a broadly Western-leaning region of the cultural map. However, different occupations introduce shifts within this region, producing distinct occupational skews. This indicates that occupational prompts are not treated as neutral role labels, but instead elicit structured value patterns. These findings extend survey-based evaluation of cultural bias beyond nationality-based prompting and provide a framework for studying how occupational personas shape value expression in LLMs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
