# Davinci the Dualist: the mind-body divide in large language models and in human learners

arXiv: https://arxiv.org/abs/2305.07667 · HTML: https://mlsanity.com/paper/2305.07667/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 67 references that are in the map.
- First posted on arXiv 10 May 2023.

## Builds on (most cited first, 7 of 7)

- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [Using cognitive psychology to understand GPT-3](https://mlsanity.com/paper/2206.14576/) (2022)
- [Neural Theory-of-Mind? On the Limits of Social Intelligence in Large LMs](https://mlsanity.com/paper/2210.13312/) (2022)
- [Identifying and Reducing Gender Bias in Word-Level Language Models](https://mlsanity.com/paper/1904.03035/) (2019)
- [The Debate Over Understanding in AI's Large Language Models](https://mlsanity.com/paper/2210.13966/) (2022)
- [Do Large Language Models know what humans know?](https://mlsanity.com/paper/2209.01515/) (2022)
- [Diminished Diversity-of-Thought in a Standard Large Language Model](https://mlsanity.com/paper/2302.07267/) (2023)

## Abstract (arXiv)

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.