From Digital Divides to Algorithmic Governance – AI and the Reproduction of Educational Inequalities

Abstract

[EN]Artificial intelligence (AI) is rapidly transforming educational systems, reshaping how knowledge is produced, evaluated, and governed. Far from being a neutral technological enhancement, AI operates as a socio-technical infrastructure embedded in power relations that redistribute opportunities unequally across students, schools, and territories. This chapter analyzes the role of AI in the reproduction of educational inequalities from a sociological perspective, emphasizing how algorithmic systems amplify digital divides, reinforce structural and cultural biases, and introduce new forms of algorithmic governance that reshape agency, autonomy, and pedagogical decision-making. The discussion develops three interconnected analytical dimensions: the emergence of digital and algorithmic capital as forms of distinction that privilege advantaged learners; the reproduction of inequality through biased data, discriminatory predictions, and exclusionary platform design; and the rise of algorithmic governmentality, in which surveillance, metric-based accountability, and automated decision-making displace teachers’ professional judgment and shape student subjectivities through normalization and control. The chapter argues that addressing these dynamics requires ethical and political frameworks that prioritize transparency, accountability, inclusion, and democratic participation in the design and governance of AI in education. It concludes by calling for critical algorithmic literacy, participatory policy design, and culturally situated approaches capable of transforming AI into a tool for educational justice rather than a mechanism that reinforces existing hierarchies.