This paper examines how Artificial Intelligence (AI) shapes the reproduction of educational inequalities from a sociological perspective. It argues that AI systems are not neutral tools but socio-technical artifacts embedded in power relations that influence knowledge, pedagogical practices, and structures of legitimacy.The analysis highlights three dimensions through which inequality is reproduced: digital divides that go beyond access and include skills and algorithmic literacy; structural and cultural biases embedded in AI processes such as admission, assessment, and adaptive learning; and algorithmic governmentality, which governs education through surveillance, metrics, and automated feedback, producing new forms of subjectivity oriented toward efficiency rather than critical thinking.The article concludes that AI in education is an ethical and political challenge. It calls for inclusive and contextualized platform design, critical training for teachers, participatory co-design of evaluation systems, and governance mechanisms that ensure transparency and accountability. From the sociology of education, promoting digital environments that are democratic, inclusive, and emancipatory is essential to achieve educational justice in the age of AI.
Elena-María García-Alonso (Sun,) studied this question.