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A relational sociology of large language models in education

This paper with Morten Hansen is out now in the British Journal of Sociology of Education:

Generative artificial intelligence products are often heralded as a solution to the problems of education bureaucracies by providing individualised learning opportunities in a cost-effective way. We posit that this claim has not been critically examined from a relational and material sociological perspective. In this conceptual paper we therefore mobilise a relational and material sociology to query the relational potentials of large language models (LLMs) as compared to more traditional education tools. We conclude that the appeal of LLM tools like ChatGPT resides in their seemingly endless mutability, i.e. the tools appear to change to respond to their users’ needs. The relational challenge is to ensure that this apparent movement on the part of the tool does not lead to stasis on the part of the learner. Our discussion brings to the fore the often forgotten cognitive and pedagogical functions of seemingly ‘dumb’ and static learning tools.

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