GENERATIVE ARTIFICIAL INTELLIGENCE IN INCLUSIVE EDUCATION: ETHICAL, PEDAGOGICAL AND LEGAL CHALLENGES FOR ENSURING THE RIGHT TO LEARNING
DOI:
https://doi.org/10.66104/mndgh586Keywords:
Generative artificial intelligence. Inclusive education. Educational ethics. Right to learning. Educational technologies.Abstract
The emergence of generative artificial intelligence has brought about profound transformations in contemporary educational systems, particularly regarding pedagogical practices, the technological mediation of learning, and the redefinition of institutional responsibilities in ensuring the right to education. In the context of inclusive education, these technologies assume strategic relevance by expanding possibilities for teaching personalization, cognitive accessibility, and curricular adaptation for students with specific educational needs. However, alongside pedagogical opportunities, ethical, legal, and epistemological challenges arise that demand critical reflection and careful regulation. This article analyzes the incorporation of generative artificial intelligence in inclusive education from an interdisciplinary perspective, articulating contributions from pedagogy, technological ethics, and educational law. The central problem guiding this investigation concerns understanding how the use of generative artificial intelligence systems can contribute to realizing the right to learning in inclusive contexts without compromising the ethical, pedagogical, and legal principles that structure democratic education. Methodologically, this is a qualitative, exploratory, and descriptive study based on a systematic literature review on artificial intelligence, educational technologies, and inclusion policies. The analysis shows that tools based on generative artificial intelligence have significant potential to support pedagogical adaptation processes, the production of accessible materials, formative feedback, and the development of personalized educational practices. However, risks related to algorithmic opacity, the reproduction of discriminatory biases, technological dependency, and the weakening of teacher autonomy are also identified. In the legal field, the need to align the use of these technologies with normative frameworks that ensure the right to inclusive education is evident, including Brazilian special education legislation and international guidelines on data protection and digital ethics. It is concluded that the responsible integration of generative artificial intelligence in inclusive education requires clear public policies, critical teacher education, and the development of ethical principles to guide the implementation of these technologies, ensuring that their use is genuinely committed to promoting educational equity and consolidating the right to learning for all students.
Downloads
References
BIONI, Bruno Ricardo. Proteção de dados pessoais: a função e os limites do consentimento. 2. ed. São Paulo: Thomson Reuters Brasil, 2021.
BRASIL. Lei nº 13.146, de 6 de julho de 2015. Lei Brasileira de Inclusão da Pessoa com Deficiência (Estatuto da Pessoa com Deficiência). Brasília: Presidência da República, 2015.
BRASIL. Lei nº 13.709, de 14 de agosto de 2018. Lei Geral de Proteção de Dados Pessoais (LGPD). Brasília: Presidência da República, 2018.
DONEDA, Danilo. Da privacidade à proteção de dados pessoais. 2. ed. São Paulo: Thomson Reuters Brasil, 2020.
FLORIDI, Luciano et al. AI4People: an ethical framework for a good AI society. Minds and Machines, v. 28, n. 4, p. 689-707, 2021. DOI: https://doi.org/10.1007/s11023-018-9482-5
GIL, Antônio Carlos. Métodos e técnicas de pesquisa social. 7. ed. São Paulo: Atlas, 2021.
HOLMES, Wayne; BIALIK, Maya; FADEL, Charles. Artificial intelligence in education: promises and implications for teaching and learning. Boston: Center for Curriculum Redesign, 2021.
HOLMES, Wayne; TUOMI, Ilkka. State of the art and practice in AI in education. European Journal of Education, v. 57, n. 4, p. 542-570, 2022. DOI: https://doi.org/10.1111/ejed.12533
LOCATELLI, Rodrigo Leite et al. Tecnologia assistiva na educação inclusiva: inovação, acessibilidade e práticas pedagógicas contemporâneas. Revista Ilustração, v. 7, p. 19-30, 2026. DOI: https://doi.org/10.46550/ilustracao.v7i3.550
LUCKIN, Rose. Machine learning and human intelligence: the future of education for the 21st century. London: UCL Institute of Education Press, 2021.
MANTOAN, Maria Teresa Eglér. Inclusão escolar: o que é? Por quê? Como fazer? 3. ed. São Paulo: Summus, 2020.
MORAN, José Manuel. Metodologias ativas para uma educação inovadora. Porto Alegre: Penso, 2022.
O'NEIL, Cathy. Weapons of math destruction: how big data increases inequality and threatens democracy. New York: Crown Publishing, 2020.
PAIXÃO, Joelson Lopes. Inteligência artificial e personalização do ensino: revisão sistemática da literatura. Revista Tópicos, v. 3, p. 1-27, 2025a.
PAIXÃO, Joelson Lopes. Uso ético da inteligência artificial em contextos educacionais. Revista Tópicos, v. 3, p. 1-20, 2025b.
PAIXÃO, Joelson Lopes et al. Inteligência artificial e autoria acadêmica: implicações éticas, epistemológicas e normativas para a produção científica contemporânea. Revista OWL Journal, v. 4, p. 1-19, 2026.
RIBEIRO, Ana Elisa; CYSNEIROS, Paulo Gileno. Tecnologias digitais e educação: desafios contemporâneos. Recife: EDUFPE, 2023.
SELWYN, Neil. Education and technology: key issues and debates. 3. ed. London: Bloomsbury Academic, 2022. DOI: https://doi.org/10.5040/9781350145573
UNESCO. Recommendation on the ethics of artificial intelligence. Paris: UNESCO, 2021.
VERGARA, Sylvia Constant. Projetos e relatórios de pesquisa em administração. 16. ed. São Paulo: Atlas, 2022.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Joelson Lopes da Paixão, Weverton Junior de Villa Silva, Rosangela Vieira Batista, Sebastião Caio dos Santos Dantas, Luís Eduardo de Sena dos Santos, João Vitor Takehiko Rodrigues Yryu, Nycollas Stefanello Vianna
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish in this journal agree to the following terms:
Authors retain copyright and grant the journal the right of first publication, with the work simultaneously licensed under the Creative Commons Attribution License, which permits the sharing of the work with proper acknowledgment of authorship and initial publication in this journal;
Authors are authorized to enter into separate, additional agreements for the non-exclusive distribution of the version of the work published in this journal (e.g., posting in an institutional repository or publishing it as a book chapter), provided that authorship and initial publication in this journal are properly acknowledged, and that the work is adapted to the template of the respective repository;
Authors are permitted and encouraged to post and distribute their work online (e.g., in institutional repositories or on their personal websites) at any point before or during the editorial process, as this may lead to productive exchanges and increase the impact and citation of the published work (see The Effect of Open Access);
Authors are responsible for correctly providing their personal information, including name, keywords, abstracts, and other relevant data, thereby defining how they wish to be cited. The journal’s editorial board is not responsible for any errors or inconsistencies in these records.
PRIVACY POLICY
The names and email addresses provided to this journal will be used exclusively for the purposes of this publication and will not be made available for any other purpose or to third parties.
Note: All content of the work is the sole responsibility of the author and the advisor.
