Exploring AI-Based Support in Speech-Language Pathology for Culturally and Linguistically Diverse Children

Speech-language pathologists (SLPs) provide support to children with speech and language difficulties through delivering evaluation, assessment, and interventions. Despite growing research on how Artificial Intelligence (AI) can support SLPs, there is limited research examining how AI can assist SLPs in delivering equitable care to culturally and linguistically diverse (CLD) children with disabilities. Through interviews with 15 SLPs and a two-part survey study with 13 SLPs, we report on SLP challenges in delivering responsive care to CLD children with disabilities (i.e., unrepresentative materials, unreliable translation, insufficient support for language variations), areas for AI-based support, evaluations of how available AI performs in addressing these challenges, and bias assessments of AI-generated materials. We discuss implications of contextually unaware AI, the range of care in AI-prompting, tensions and tradeoffs of AI-based support, and honoring diverse representations in AI-generated materials. We offer considerations for SLPs using AI-based tools and general-purpose AI in their practice.