Artificial Intelligence in Education: Between Inclusion and Marginalization
Abstract
The rapid development of artificial intelligence (AI) is transforming educational practices within increasingly hybrid learning environments, raising questions about its role in shaping inclusion and marginalisation. The article aims to identify and interpret the mechanisms through which AI in education simultaneously supports inclusion and generates processes of marginalisation. The study is based on a critical and interpretative literature review drawing on pedagogy, sociology of education, and technology and data studies. The analysis included both contemporary empirical research and classical theoretical frameworks (e.g., Bourdieu, Foucault, Znaniecki). The findings indicate that AI can enhance the individualisation of learning and improve access to educational resources. At the same time, it may reproduce existing inequalities, reinforce labelling processes, and intensify surveillance practices. Inclusion and marginalisation emerge as coexisting dimensions of the same educational processes, dependent on the ways AI is implemented and interpreted in institutional contexts. The inclusive potential of AI is not inherent to the technology itself but results from specific pedagogical and institutional practices. From a humanistic perspective, the key challenge lies in ensuring that data-driven systems support student agency, dignity, and equitable participation rather than reinforce mechanisms of control and exclusion.
Keywords:
artificial intelligence in education, datafication of education, humanistic coefficient, educational inclusion, marginalizationReferences
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