ARTIFICIAL INTELLIGENCE AND NEURODIVERSITY: POTENTIALS AND RISKS FOR STUDENTS WITH ADHD AND ASD

Abstract

This chapter examines the potentials and risks of using artificial intelligence in the education of neurodivergent students, particularly those with ADHD and ASD. The study is grounded in a narrative literature review and aims to understand how AI-based tools can either support or compromise processes of learning, autonomy and inclusion. The methodology involved the selection, organization and analytical synthesis of works on neurodiversity, inclusive education, algorithmic ethics and educational technologies. Results indicate that AI offers meaningful possibilities for cognitive accessibility, personalized scaffolding and multimodal communication, especially through tools that assist executive function for students with ADHD and support communication and predictability for autistic learners. However, the literature also reveals significant risks related to surveillance, biased datasets, behavioral normalization, cognitive dependency and extensive data collection affecting vulnerable populations. These issues are intensified in datified school environments where algorithms classify and track students. The study concludes that AI can contribute to more inclusive and equitable educational experiences only when its use is critically mediated by teachers and aligned with ethical principles that protect autonomy, dignity and the right to learn according to diverse cognitive profiles. Critical teacher education, strong data protection policies and a commitment to cognitive justice are essential to ensure that AI supports rather than undermines neurodivergent students.