4E cognition and the coevolution of human–AI interaction

This paper argues that large language models (LLMs) should be understood not as objects but as processual and relational phenomena that co-constitute human agency within a shared sociotechnical environment. Drawing on 4E cognition (embodied, embedded, enactive, and extended), the authors propose reframing AI as an interactive medium of enactive and extended human action. They offer a 4E-compatible connectionist account that views AI as a co-evolving component of the extended cognitive ecology, shaped by and shaping enactive practices, intentions, and norms. The paper also discusses AI's limits, addressing hallucination and model collapse from this perspective.

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Abstract

Abstract This paper examines the interaction between humans and large language models (LLMs) through the lens of 4E cognition, which encompasses embodied, embedded, enactive, and extended cognitive processes, to provide a comprehensive understanding of their relational dynamics. It argues that LLMs should not be conceived of in terms of objects but be understood as a processual and relational phenomenon that co-constitutes human agency in a shared sociotechnical environment. As such, the paper reframes AI as an interactive medium of enactive and extended human action. By focusing on the relational entanglement of social databases, dynamic patterns, and algorithmic structures, the paper proposes a 4E-compatible connectionist account of AI—one that understands AI not only as a technological artifact but as a co-evolving component of the extended cognitive ecology of human life, shaping and shaped by enactive practices, intentions, and norms. Finally, the paper discusses the limits of AI, discussing the problem of AI hallucination and collapse from a 4E cognition perspective.