Underrepresented students and artificial intelligence
DOI:
https://doi.org/10.31637/epsir-2025-843Keywords:
artificial intelligence; machine learning; education; subrepresentation; discrimination; inclusion; fundamental rights; public policies., Artificial Intelligence, machine learning, education, subrepresentation, discrimination, inclusion, Human rights, Public politicsAbstract
Introduction: Educators, public administration, and governments need to be aware of the strengths and weaknesses of AI in learning, in order to be empowered, not dominated by technology, in digital citizenship education practices, especially with minorities and/or underrepresented students, because it could increase the social and digital divide. Methodology: This study uses the PRISMA methodology and analyzes data obtained from the Web of Science and Google Scholar. Results: It is analyzed whether errors, biases, underrepresentation and discrimination occur, or these systems contribute to inclusion; their interest in the scientific community and main normative and ethical challenges through numerous examples. Discussion: The findings underscore the importance of its implementation, the paucity of research in this area, the opportunities, harmful practices and their effects, and the challenges to be met. Conclusions: This analysis underlines its effect in other areas such as labor, its importance in relation to fundamental rights, and the impact on our own models of social and democratic rule of law.
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