Artificial intelligence in education: uses, advantages, risks, and the need for pedagogical regulation
DOI:
https://doi.org/10.69849/9rj1k549Keywords:
artificial intelligence, education, pedagogical regulation, educational technology, ethics in educationAbstract
This article examines, from a theoretical-analytical perspective, the incorporation of artificial intelligence (AI) systems in contemporary educational contexts, with emphasis on technological deployment, the pedagogical advantages identified in the specialized literature, the epistemological, ethical and social risks arising from this in- corporation and, above all, the urgency of a careful pedagogical regulation. Based on a bibliographic review grounded in reference authors in the field of education, educational technology and philosophy of science, it is argued that the uncritical adoption of intelligent technologies in school practices may deepen structural inequalities and undermine students' cognitive autonomy. It is concluded that the pedagogical regula - tion of AI, grounded in ethical, epistemological and democratic principles, constitutes an unavoidable imperative for such technologies to fulfil an emancipatory rather than merely instrumental function.
References
BENDER, Emily M. et al. On the dangers of stochastic parrots: can language models be too big? In: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. New York: ACM, 2021. p. 610-623.
BIESTA, Gert. The Rediscovery of Teaching. New York: Routledge, 2017.
BLOOM, Benjamin S. The 2 sigma problem: the search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, Washing- ton, v. 13, n. 6, p. 4-16, 1984.
FEENBERG, Andrew. Transforming Technology: a critical theory revisited.
New York: Oxford University Press, 2002.
FREIRE, Paulo. Pedagogia da Autonomia: saberes necessários à prática educativa.
São Paulo: Paz e Terra, 1996.
HATTIE, John; TIMPERLEY, Helen. The power of feedback. Review of Educational Research, Washington, v. 77, n. 1, p. 81-112, 2007.
HOLMES, Wayne et al. Artificial Intelligence in Education: promises and im- plications for teaching and learning. Boulder: Creative Education Foundation, 2019.
LONGPRE, Shayne et al. The Data Provenance Initiative: a large scale audit of dataset licensing and attribution in AI training. arXiv, 2023. Disponível em: https://arxiv.org/abs/2310.16787. Acesso em: 10 fev. 2025.
LUCKIN, Rose et al. Intelligence Unleashed: an argument for AI in education.
London: Pearson Education, 2016.
MISHRA, Punya; KOEHLER, Matthew J. Technological pedagogical content knowledge: a framework for teacher knowledge. Teachers College Record, New York,
v. 108, n. 6, p. 1017-1054, 2006.
O'NEIL, Cathy. Weapons of Math Destruction: how big data increases inequality and threatens democracy. New York: Crown Publishers, 2016.
PEDRO, Francesc et al. Artificial Intelligence in Education: challenges and opportunities for sustainable development. Paris: UNESCO, 2019.
RAMOS, Daniela Karine. Tecnologias na educação: reflexões sobre o uso da inteligência artificial. Educação em Revista, Belo Horizonte, v. 36, p. 1-24, 2020.
SELWYN, Neil. Should Robots Replace Teachers? AI and the future of edu- cation.
Cambridge: Polity Press, 2019.
SIEMENS, George; LONG, Phil. Penetrating the fog: analytics in learning and education.
EDUCAUSE Review, Boulder, v. 46, n. 5, p. 30-40, 2011.
UNESCO. Recommendation on the Ethics of Artificial Intelligence. Paris: UNESCO, 2021. Disponível em:
https://unesdoc.unesco.org/ark:/48223/pf0000381137. Acesso em: 12 fev. 2025.
VANLEHN, Kurt. The relative effectiveness of human tutoring, intelligent tuto- ring systems, and other tutoring systems. Educational Psychologist, Philadelphia, v. 46, n. 4, p. 197-221, 2011.
WILLIAMSON, Ben. Big Data in Education: the digital future of learning, policy and practice. London: SAGE Publications, 2017.
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Copyright (c) 2026 Jordilson Souza, Antônio Nobre, Claudio Campos, Glaucia Costa (Autor)

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