Interactive Design with Autistic Children using LLM and IoT for Personalized Training: The Good, The Bad and The Challenging
Yongfu Wang, Mingyue Tang, Yifan He, Tiffany Y. Tang · 2024
The advent of generative artificial intelligence technologies, such as Large Language Models (LLMs) and Large Vision Models (LVMs), has shown promising results in both academic and industrial sectors, leading to widespread adoption. However, there has been limited focus on applying these technologies to assist children with special needs like Autism Spectrum Disorder (ASD). Meanwhile, conventional personalized training with interactive design for children with special needs continues to face significant challenges with traditional approaches. This workshop aims to provide a platform for researchers, software developers, medical practitioners, and designers to discuss and evaluate the benefits and drawbacks of using LLMs and the Internet of Things (IoT) for the diagnosis and personalized training of autistic children. Through a series of activities, including oral presentations, demonstrations, and panel discussions, this half-day workshop seeks to foster a network of experts dedicated to improving the lives of children with special needs and to inspire further research on leveraging emerging ubiquitous technologies for these underprivileged users, their caregivers and special education teachers.