Abstract

Objectives: The purpose of this article is to explore the use of artificial intelligence technologies for the diagnosis and treatment of early childhood autism. Methods: The methodology used is an interdisciplinary and multi-level approach, highlighting the use of artificial intelligence for the diagnosis and treatment of autism at the social, individual, and psychophysiological levels. Results: The main prompt-queries for generating developmental tasks and corrective exercises using a neural network have been identified. A hypothesis has been put forward about the importance of taking into account the psychophysiological mechanisms of childhood autism using artificial intelligence models, and new research directions and ways of their practical application have been outlined. Conclusions: New approaches have been proposed to address the issues of inappropriate use of artificial intelligence in the analysis of autistic children and potential violations of ethical standards.