Values are a basic driving force underlying human behavior. Large Language Models (LLM) technology is constantly improving towards human-like dialogue. However, little research has been done to study the values exhibited in text generated by LLMs. Here we study this question by turning to the rich literature on value structure in psychology. We ask whether LLMs exhibit the same value structure that has been demonstrated in humans, including the ranking of values, and correlation between values. We show that the results of this analysis strongly depend on how the LLM is prompted, and that under a particular prompting strategy (referred to as 'Value Anchoring') the agreement with human data is quite compelling. Our results serve both to improve our understanding of values in LLMs, as well as introduce novel methods for assessing consistency in LLM responses.

翻译：价值观是人类行为的基本驱动力。大型语言模型（LLM）技术正不断向类人对话方向演进。然而，目前鲜有研究关注LLM生成文本中所展现的价值观。本研究借助心理学中关于价值结构的丰富文献探讨此问题，通过分析LLM是否呈现与人类相似的价值结构——包括价值观排序及价值观间的相关性。研究表明，分析结果高度依赖于提示策略的设计，在特定提示方法（称为"价值锚定"）下，LLM与人类数据的契合度尤为显著。本研究成果既深化了对LLM价值观的理解，也为评估LLM响应一致性提供了创新方法论。