AI 中文总结
本研究依托欧洲社会调查，发现LLMs与不同社会人口学群体的价值观对齐存在差异，国籍作为单独变量的解释力与全部社会人口学变量相当，国家与社会人口学因素在解释对齐模式上互补。
AI 中文摘要
随着大型语言模型（Large Language Models, LLMs）日益成为信息与建议的主要来源，理解其在价值观层面与人类的对齐情况成为紧迫问题。越来越多的文献利用大规模调查研究LLMs与人类所表述的价值观和观点的对齐程度，除少数例外情况，研究人群均以国界或文化边界定义。然而，这一研究重点忽视了社会人口学差异可能对价值对齐差异产生的作用。本研究依托欧洲社会调查，针对10款主流商用LLM，结合15项社会人口学变量及居住国，探究上述知识缺口。分析显示，LLMs与不同社会人口学群体的价值观对齐情况确实存在差异，尤其在教育、收入、职业和宗教等维度的群体中表现明显。在个体层面考察对齐情况时，仅作为单独变量的受访者国籍，所能解释的差异量与全部考察的社会人口学变量相当。进一步解耦国家层面与社会人口学因素的各自作用后，发现二者在解释价值对齐模式上具有互补性，且其相对权重随所考察问题子集的不同而变化。
英文摘要
As Large Language Models (LLMs) are increasingly used as a primary source of information and advice, understanding their alignment to humans in terms of values becomes a pressing concern. A growing literature has leveraged large scale surveys to investigate to what extent LLMs' and humans' stated values and opinions align. With limited exceptions, studied populations have been defined country borders or cultural bounds. Yet, this focus neglects the role that socio-demographic divides may play for value alignment disparities. Relying on the European Social Survey, we address this knowledge gap by considering value alignment displayed with respect to 10 prominent commercial LLMs in terms of 15 socio-demographic variables as well as country of residence. Our analyses reveal that LLMs are indeed unequally aligned to the values of different socio-demographic groups, notably those defined by education, income, occupation and religion. When examining alignment at the individual level, a respondent's country, taken as a stand-alone variable, explains a substantial amount of variation that is on par with the full set of considered socio-demographics. Further disentangling the respective role of country-level and socio-demographic factors, we find they are complementary in explaining value alignment patterns, with their relative weights varying across the subset of questions considered.
CommentsAccepted at AIES 2026 (9th AAAI/ACM Conference on AI, Ethics, and Society)
