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，人类是天生的二元论者——他们认为心灵是虚幻缥缈的，与身体截然不同。过往研究也显示，二元论部分是通过学习涌现的（例如，Barlev & Shtulman, 2021）。然而，学习本身是否足以产生二元论尚未可知。来自人类学习者的证据无法解答这一问题，因为人类不仅具备一般学习能力，还拥有核心知识能力。近期研究结果表明，核心知识会催生二元论（Berent, Theodore & Valencia, 2021; Berent, 2023）。为评估学习的作用，本文在达芬奇（Davinci）——一个不具备任何先天核心知识的大语言模型（LLM）——中探究身心二分现象。我们证明，达芬奇仍倾向于二元论，且这种倾向随学习者归纳潜能的增强而系统性地增加。因此，达芬奇（GPT-3模型）表现出轻微的二元论倾向，而其后续版本text-davinci-003（GPT-3.5模型）则展现出全面的偏见。该模型有选择地将思想（认知状态）视为非实体化的——它们不太可能出现在身体中（大脑中），但也不会在身体消失后（死后）消失。尽管达芬奇的性能受限于其句法能力，且与人类存在差异，但其二元论偏见是稳健的。这些结果表明，身心二分在一定程度上可从经验中习得，同时也揭示了当LLM暴露于人类叙事时，它们不仅会归纳出人类知识，还会归纳出人类偏见。