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.

人类行为的基本驱动力是价值观。大型语言模型 (LLM) 技术不断向与人类对话类似的方向发展。然而，目前在研究 LLM 生成的文本中所展示的价值观方面的研究仍很少。本研究通过借鉴心理学中丰富的关于价值观结构的文献来探索这个问题。我们研究了LLM是否表现出与人类相同的价值观结构，包括价值观排序和价值观之间的相关性。我们展示出，对LLM进行提问的方式在结果上会产生较大差异，而在一种特定的提示策略下（称为“价值定锚”），与人类数据的一致性非常强烈。本研究结果不仅有助于提高我们对LLM中价值观的理解，还引入了新的评估LLM响应一致性的方法。

LLMs是否具有一致的价值观？