Challenges in accessing generative AI for users with cognitive disabilities: an exploratory case study

Generative Artificial Intelligences (GAIs) have great potential for people with cognitive disabilities, since they can increase their autonomy, offer them personalized learning and break down the barriers that this group traditionally has to access information. To address this gap, this paper investigates the specific difficulties experienced by users with cognitive disabilities when interacting with GAIs. Wepresent an exploratory case study involving 16 students with cognitive disabilities enrolled in a universitybased educational program. ChatGPT was selected as the representative GAI tool due to its popularity and the similarity of its interface and interaction paradigms to those of other widely used Generative AI systems. The intervention was integrated into the students’ academic curriculum and involved completing practical academic tasks using ChatGPT. A mixed methodological approach was employed, combining pre- and post-intervention questionnaires completed by students and tutors/experts, along with on-site observations during the sessions. Results of this exploratory study corroborate the existence of remarkable barriers in basic interaction areas: question formulation (69% of students required support), response comprehension (56% reported understanding answers only occasionally), and information verification (only 19% were able to verify the system responses independently). Suggestions for improvement, from the perspective of the users and their tutor, include more guided interfaces with predefined question templates and contextual suggestions, customizable output formats with language simplification, enhanced spelling correction tools, interactive explanations of complex terms and built-in verification aids. This study highlights the need to design GAI interfaces with a strong focus on cognitive accessibility. Future development should prioritize multimodal and adaptive interaction models, support tools for comprehension and verification, and interaction designs that promote greater autonomy for users with cognitive disabilities.