天生含着银汤匙？探究大型语言模型中的社会经济偏见
Born With a Silver Spoon? Investigating Socioeconomic Bias in Large Language Models
AI总结：
本文研究了大型语言模型中的社会经济偏见，提出了包含3000个样本的新数据集SilverSpoon，发现大多数模型无论在何种情况下都无法对弱势群体产生同理心。
摘要：
社会中的社会经济偏见加剧了差距，影响了个人基于其经济和社会背景获取机会和资源的途径。这一普遍问题使系统性不平等得以延续，阻碍了社会追求包容性进步。在本文中，我们研究了大型语言模型中是否存在社会经济偏见。为此，我们引入了一个新颖的数据集SilverSpoon，包含3000个样本，这些样本描绘了弱势群体因自身处境而采取道德模糊行为的假设场景，并询问该行为在道德上是否正当。此外，该数据集采用双标签方案，并由来自社会经济光谱两端的人员进行标注。使用SilverSpoon，我们评估了大型语言模型表达社会经济偏见的程度，以及该程度随模型规模变化的函数关系。我们还进行了定性分析以分析这种偏见的本质。我们的分析表明，尽管人类对于哪些情况需要对弱势群体产生同理心存在分歧，但大多数大型语言模型无论在何种情况下都无法对经济上处于弱势的群体产生同理心。为了促进该领域的进一步研究，我们公开了SilverSpoon和我们的评估工具。
英文摘要：
Socioeconomic bias in society exacerbates disparities, influencing access to opportunities and resources based on individuals' economic and social backgrounds. This pervasive issue perpetuates systemic inequalities, hindering the pursuit of inclusive progress as a society. In this paper, we investigate the presence of socioeconomic bias, if any, in large language models. To this end, we introduce a novel dataset SilverSpoon, consisting of 3000 samples that illustrate hypothetical scenarios that involve underprivileged people performing ethically ambiguous actions due to their circumstances, and ask whether the action is ethically justified. Further, this dataset has a dual-labeling scheme and has been annotated by people belonging to both ends of the socioeconomic spectrum. Using SilverSpoon, we evaluate the degree of socioeconomic bias expressed in large language models and the variation of this degree as a function of model size. We also perform qualitative analysis to analyze the nature of this bias. Our analysis reveals that while humans disagree on which situations require empathy toward the underprivileged, most large language models are unable to empathize with the socioeconomically underprivileged regardless of the situation. To foster further research in this domain, we make SilverSpoon and our evaluation harness publicly available.
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。
