AI in Autism Screening

Autism spectrum disorder is identified through developmental history and behavior; no single blood test or imaging scan diagnoses it. CDC explains screening tools can identify children who may need evaluation, while diagnostic assessment draws on caregiver descriptions of development and professional observation of behavior. AI research may analyze questionnaires, speech, movement, or video, but a model score should not be presented as diagnosis or a substitute for qualified evaluation. Performance depends on age, language, culture, disability, and collection setting. A tool tested in one group may not work as well in another. Video or speech analysis raises privacy and consent questions, especially for children. Families should know what data are collected, who can access them, and how long they are retained. A negative score should not dismiss persistent concerns, and a positive score should connect to follow-up rather than stigma. Health systems should use tools with evidence for the intended age group and workflow, explain uncertainty, and monitor who is referred and who receives services. CDC guidance describes further developmental and medical evaluation when screening identifies concern. Access to evaluation and support matters as much as the screen itself. AI may help organize observations or reduce administration, but diagnosis and services require human assessment and family partnership. Build processes that explain what a screen can do, what it cannot do, and where families can ask questions about the next step.