Artificial intelligence for neuro inclusion: reflections in the age of the autistic barbie
A few months ago, Mattel, in collaboration with the Autistic Self Advocacy Network, created a version of Barbie equipped with accessories widely used by nonverbal autistic people, such as the Smart Tab and noise-canceling headphones. Setting aside the debate about the actual usefulness and authenticity of the project, we believe it provides important reflections. What clearly emerges is that the widespread distribution of the famous doll helps shed light on neurodiversity among younger people and highlights the key role played by technologies, which become real electronic extensions that help facilitate the daily lives of many neurodivergent individuals. In fact, for nonverbal neurodivergent people, image-based forms of communication are essential to interact with others and to experience daily life more calmly.
In this context, what role can AI play? It has undoubtedly established itself as an innovative technology applied in numerous fields, including education, transportation, and communication. Among the areas where its social impact is particularly significant is that of assistive technologies for people with disabilities. According to a WHO estimate (2022), more than 1.3 billion people worldwide live with some form of disability. This figure highlights how individuals with physical and cognitive disabilities, in many contexts, face difficulties in accessing information, services, and full participation in working and collective life.
Recent research shows that neuroinclusion processes are receiving increasing attention from companies (Ernst & Young Global Limited, 2025). In educational and work environments that are not adequately adapted, these differences translate into conditions of functional disadvantage. Compensatory tools and assistive technologies enabled by AI can represent essential support in breaking down some of the barriers that prevent full participation in social and professional life for people experiencing disability and/or neurodivergence. The film industry offers fascinating (and moving) examples of experiences related to the world of autism. One need only think of the film Life, Animated, in which the protagonist Owen loses his verbal abilities at a young age and only several years later, thanks to the habit of watching Disney films with his brother, begins to produce sounds and words again. Gradually, the film and the dialogues of the animated scenes become a bridge tool for this autistic child and help him interpret the world around him. Today he is an adult, verbal, able to work and live independently. If Disney films represented a support for the boy—while requiring several years to change his experience—one can imagine the infinite application possibilities that AI could have offered Owen to accelerate changes in some of his brain functions, potentially requiring months instead of years. For example, AI could have provided real-time analyses of Owen’s interest patterns, identifying which recurring verbal expressions of characters, repetitions, and preferences he responded to best, and then generating outputs such as automatic recognition of themes, characters, recurring phrases, or targeted suggestions for caregivers and therapists based on objective data.
In the next five years, machine learning (ML) and natural language processing (NLP) algorithms will increasingly represent effective solutions for content personalization, adaptation of learning pace, and support in understanding and organizing information. If properly integrated into organizations, they can contribute to creating more accessible, equitable, and respectful environments for different ways of learning and interacting with the world. However, it remains fundamentally important to develop awareness of the limits of AI tools and the ethical challenges they pose. How can AI be applied effectively and, at the same time, ethically to support neuroinclusion processes? Time (and regulation) will tell. What we strongly advocate, however, is a human-centered approach to the regulation of artificial intelligence. Without the human component guiding technological processes, the risks are far greater than the benefits.