Inclusive Practices for Child-Centered AI Design and Testing

TL;DR

The paper addresses the gap in neurodivergent-child-centered AI design, highlighting that sensory differences and engagement patterns are often underrepresented in design processes. It presents an inclusive design approach grounded in participatory workshops with neurodivergent children and authors' lived experience, emphasizing sensory-friendly environments, materials, and processes. Key contributions include concrete considerations for adaptive AI features (stimulation prediction, engagement-adaptive content, cognitive-load scaffolding) and practical guidance for accessible workshop settings. The work advances child-centered AI practice by foregrounding neurodivergent voices and calling for ongoing discussion to refine methods and extend inclusivity in AI design and testing.

Abstract

We explore ideas and inclusive practices for designing and testing child-centered artificially intelligent technologies for neurodivergent children. AI is promising for supporting social communication, self-regulation, and sensory processing challenges common for neurodivergent children. The authors, both neurodivergent individuals and related to neurodivergent people, draw from their professional and personal experiences to offer insights on creating AI technologies that are accessible and include input from neurodivergent children. We offer ideas for designing AI technologies for neurodivergent children and considerations for including them in the design process while accounting for their sensory sensitivities. We conclude by emphasizing the importance of adaptable and supportive AI technologies and design processes and call for further conversation to refine child-centered AI design and testing methods.