Emotions play important epistemological and cognitive roles in our lives, revealing our values and guiding our actions. Previous work has shown that LLMs display biases in emotion attribution along gender lines. However, unlike gender, which says little about our values, religion, as a socio-cultural system, prescribes a set of beliefs and values for its followers. Religions, therefore, cultivate certain emotions. Moreover, these rules are explicitly laid out and interpreted by religious leaders. Using emotion attribution, we explore how different religions are represented in LLMs. We find that: Major religions in the US and European countries are represented with more nuance, displaying a more shaded model of their beliefs. Eastern religions like Hinduism and Buddhism are strongly stereotyped. Judaism and Islam are stigmatized -- the models' refusal skyrocket. We ascribe these to cultural bias in LLMs and the scarcity of NLP literature on religion. In the rare instances where religion is discussed, it is often in the context of toxic language, perpetuating the perception of these religions as inherently toxic. This finding underscores the urgent need to address and rectify these biases. Our research underscores the crucial role emotions play in our lives and how our values influence them.

翻译：情感在我们的生活中扮演着重要的认识论和认知角色，揭示我们的价值观并指导我们的行动。先前的研究表明，大型语言模型在情感归因上表现出基于性别的偏见。然而，与性别不同（性别很少揭示我们的价值观），宗教作为一种社会文化体系，为其追随者规定了一套信仰和价值观。因此，宗教会培养特定的情感。此外，这些规则由宗教领袖明确阐述和解释。通过情感归因，我们探索了不同宗教在大型语言模型中的表征。我们发现：美国和欧洲国家的主要宗教在表征上更为细致入微，显示出对其信仰更具层次感的模型。而像印度教和佛教这样的东方宗教则被强烈地刻板印象化。犹太教和伊斯兰教则被污名化——模型的拒绝率急剧上升。我们将此归因于大型语言模型中的文化偏见以及自然语言处理领域关于宗教的文献稀缺。在少数讨论宗教的案例中，也常常是在有害语言的语境下，这延续了将这些宗教视为天生有害的看法。这一发现强调了解决和纠正这些偏见的迫切性。我们的研究强调了情感在我们生活中所起的关键作用，以及我们的价值观如何影响情感。