Who comes to AI already oriented? Sociotechnical belonging and curricular justice in Higher Education

Abstract

This article examines how inequalities that predate the use of generative artificial intelligence shape students’ relationships with these technologies in higher education. Rather than treating differences in performance as expressions of individual talent or mere technical mastery, the text argues that they result from unequal distributions of cultural repertoire, linguistic confidence, familiarity with systems, and authorization to experiment, revise, and sustain critical intention. Its objective is to propose the concept of sociotechnical belonging as an analytical operator for understanding why some  subjects arrive more oriented to interaction with AI than others. This is a theoretical- analytical essay grounded in Pierre Bourdieu, Sara Ahmed, Donna Haraway, Lucy  Suchman, Ruha Benjamin, and Paulo Freire. It argues, finally, that AI does not create such inequalities in isolation, but rather makes them more visible and reorganizes them, which requires universities to adopt an approach to curricular justice that goes beyond access to the tool itself and incorporates orientation, suspicion, iteration, and situated authorship.