Mechanism of Artificial Intelligence in Art Therapy for Children with Autism

Art therapy serves as an important rehabilitation approach for children with autism. However, traditional therapy models suffer from limitations such as insufficient personalization and low active participation of children, resulting in limited intervention effects. Artificial intelligence (AI), with its powerful data application capability and diverse interactive advantages, can effectively make up for the shortcomings of traditional therapy models, yet its mechanism in art therapy for children with autism remains unclear. Accordingly, this paper takes special-education teachers, experts, children with autism and their parents as research subjects, adopts the combining methods of questionnaire surveys, semi-structured interviews and behavioral observation, and conducts baseline regression analysis, mediation effect tests, moderation effect tests, and chain mediation effect test. The results show that AI (including AI data application capability and AI interaction model) can effectively improve the art therapy effect of children with autism. The fitness of personalized schemes and the participation of children exert mediating effect, while children’s age and children’s symptom degree exert moderating effects. AI empowers art therapy for children with autism through dual pathways, namely the data-adaptation pathway of “AI data application capability → fitness of personalized schemes”, and the interactive engagement pathway of “AI interaction model → children’s engagement”. Combined with this conclusion, suggestions are put forward for the application of AI in art therapy. The research of this paper reveals the transmission mechanism and boundary conditions of AI-empowered art therapy, deepens the understanding of the applicability of human-machine synergy theory in special education scenarios, and can provide theoretical guidance for optimizing the practice of intelligent art therapy for children with autism.