A large literature suggests that people are intuitive Dualists--they consider the mind ethereal, distinct from the body. Past research also shows that Dualism emerges, in part, via learning (e.g., Barlev & Shtulman, 2021). But whether learning is sufficient to give rise to Dualism is unknown.The evidence from human learners does address this question because humans are endowed not only with general learning capacities but also with core knowledge capacities. And recent results suggest that core knowledge begets Dualism (Berent, Theodore & Valencia, 2021; Berent, 2023). To evaluate the role of learning, here, we probe for a mind-body divide in Davinci--a large language model (LLM) that is devoid of any innate core knowledge. We show that Davinci still leans towards Dualism, and that this bias increases systematically with the learner's inductive potential. Thus, davinci (a GPT-3 model) exhibits mild Dualist tendencies, whereas its descendent, text-davinci-003 (a GPT-3.5 model), shows a full-blown bias. It selectively considers thoughts (epistemic states) as disembodied--as unlikely to show up in the body (in the brain), but not in its absence (after death). While Davinci's performance is constrained by its syntactic limitations, and it differs from humans, its Dualist bias is robust. These results demonstrate that the mind-body divide is partly learnable from experience.They also show how, as LLM's are exposed to human narratives, they induce not only human knowledge but also human biases.

翻译：大量文献表明，人类是直觉上的二元论者——他们认为心灵是超然的，与身体截然不同。过去的研究还表明，二元论在一定程度上是通过学习产生的（例如，Barlev & Shtulman, 2021）。然而，学习本身是否足以产生二元论尚不清楚。来自人类学习者的证据无法回答这一问题，因为人类不仅具备一般的学习能力，还拥有核心知识能力。最近的研究结果表明，核心知识会催生二元论（Berent, Theodore & Valencia, 2021; Berent, 2023）。为了评估学习的作用，本文探讨了达芬奇（Davinci）——一个缺乏任何先天核心知识的大语言模型（LLM）——中是否存在身心分离。我们发现，达芬奇仍然倾向于二元论，并且这种偏向随着学习者的归纳潜力系统性增强。因此，达芬奇（GPT-3模型）表现出轻微的二元论倾向，而其衍生模型text-davinci-003（GPT-3.5模型）则显示出完全成熟的偏向。它选择性地将思想（认知状态）视为脱离身体的——即不太可能出现在身体（大脑）中，但在身体消失后（死亡后）却可能存在。尽管达芬奇的性能受限于其句法能力，且与人类存在差异，但其二元论偏向是稳健的。这些结果表明，身心分离在一定程度上可以从经验中习得。它们还揭示了，随着大语言模型暴露于人类叙事中，它们不仅诱发了人类知识，也诱导了人类的偏见。