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A large literature suggests that people are intuitive Dualists--they considerthe mind ethereal, distinct from the body. Past research also shows thatDualism emerges, in part, via learning (e.g., Barlev & Shtulman, 2021). Butwhether learning is sufficient to give rise to Dualism is unknown.The evidencefrom human learners does address this question because humans are endowed notonly 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, weprobe for a mind-body divide in Davinci--a large language model (LLM) that isdevoid of any innate core knowledge. We show that Davinci still leans towardsDualism, and that this bias increases systematically with the learner'sinductive potential. Thus, davinci (a GPT-3 model) exhibits mild Dualisttendencies, whereas its descendent, text-davinci-003 (a GPT-3.5 model), shows afull-blown bias. It selectively considers thoughts (epistemic states) asdisembodied--as unlikely to show up in the body (in the brain), but not in itsabsence (after death). While Davinci's performance is constrained by itssyntactic limitations, and it differs from humans, its Dualist bias is robust.These results demonstrate that the mind-body divide is partly learnable fromexperience.They also show how, as LLM's are exposed to human narratives, theyinduce not only human knowledge but also human biases.

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