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arXiv:2305.16367cs.CL

Role-Play with Large Language Models

Murray Shanahan, Kyle McDonell, Laria Reynolds

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Abstract

As dialogue agents become increasingly human-like in their performance, it is imperative that we develop effective ways to describe their behaviour in high-level terms without falling into the trap of anthropomorphism. In this paper, we foreground the concept of role-play. Casting dialogue agent behaviour in terms of role-play allows us to draw on familiar folk psychological terms, without ascribing human characteristics to language models they in fact lack. Two important cases of dialogue agent behaviour are addressed this way, namely (apparent) deception and (apparent) self-awareness.

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DOI
Subjects
cs.CLComputation and Language cs.AIArtificial Intelligence cs.LGMachine Learning

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Dec 2023 to Dec 2023. Found in 1 HN submission from Jun 2023 to Jun 2023. Open submission discussions.

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    • > These things are storytellers, not teachers. I really liked how a recent paper from DeepMind put it - LLMs are just role-playing: https://arxiv.org/abs/2305.16367. This explains so much.

      dinvladView on HNParent context

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