Foregrounded by AI: What a Sociomaterial Account of Literacy Implies for Postdigital Design Orientations

Abstract This article argues that Large Language Models (LLMs) reveal literacy’s sociomaterial character: that it is constituted within more-than-human assemblages of people, texts, technologies, practices, and infrastructures, rather than in the cognitive capacity of the individual. Rather than asking what new literacies Generative Artificial Intelligence (GenAI) demands, it asks what LLMs reveal about literacy itself. This analysis draws on the sociomaterial tradition in science and technology studies, including actor-network theory, spatial perspectives, and postdigital literacy research. It reconceptualises literacy as emergent practice within assemblages, arguing that competence frameworks, by centring the individual, cannot register the distributed, infrastructural, and nonhuman dimensions of literacy that this shift makes visible. From this analysis, three design orientations for postdigital literacy environments are derived: making assemblages visible, sustaining fluid literacy spaces, and preserving conditions for critical reflexivity. The article concludes by arguing that these orientations carry political as well as pedagogical stakes, since current AI assemblages risk amplifying existing educational inequalities rather than benefiting all learners equally.