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arXiv AI By Elena C. Cuffari, Marta P\'erez-Verdugo, Xabier E. Barandiaran

Incorporating Machine-Others: An Enactive Exploration of Human-LLM Interactions

Read the original on arXiv AI →

The paper argues that new interactional concepts are needed to understand how humans change when engaging with large language models (LLMs). Drawing on enactive theory and the notion of Linguistic Bodies, it proposes that humans incorporate LLMs both as tools that enable specific skills and as linguistic partners that shape identity and language use. The authors introduce the idea of "susceptive sense‑making" to describe the heightened semiotic labor involved when friction is absent in these interactions, and suggest that this dynamic may affect users’ autonomy and development.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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