Recommendations for the Development and Implementation of Generative Artificial Intelligence Tools in Pediatric...

The integration of generative artificial intelligence (GenAI) into pediatric health care offers exciting opportunities alongside critical challenges. GenAI tools, like large language models (LLMs), show promise in several health care applications, including but not limited to clinical decision support, documentation, and medical education across a wide range of pediatric subspecialties. However, real-world validation remains limited, and concerns persist around accuracy, bias, reliability, sustainability, and durability. Studies indicate that LLMs, when applied to pediatrics, often underperform compared with adult medical specialties, raising questions about their readiness for use in the care of children and adolescents. Moreover, the risk of exacerbating health disparities among patients of various races, ethnicities, genders, languages, abilities, and socioeconomic statuses because of biased or nonrepresentative training data underscores the need for rigorous oversight and accountability. This policy outlines recommendations for the safe, equitable, and effective use of GenAI in pediatric settings. Developers should prioritize diverse pediatric data sets, proactively address bias, and implement strong data privacy and security safeguards. Health care institutions must establish rigorous validation protocols, ensure compliance with privacy regulations, and maintain clear human oversight. Relevant regulatory and oversight bodies should enforce pediatric-specific evaluations and require postmarket surveillance. Governance frameworks must support interdisciplinary collaboration, transparency, and education initiatives to equip pediatricians with GenAI literacy. Reasonable disclosure of GenAI involvement in patient care is essential to establish and strengthen trust. GenAI policies pertaining to the care of children and adolescents must remain adaptive to ensure ethical, equitable, and evidence-based implementation. Despite these numerous challenges, GenAI holds transformative potential to improve pediatric health outcomes, and this policy seeks to empower developers, researchers, and clinicians to responsibly build and harness this technology.