DevAI: Developmental Perspectives on AI

How does intelligence form? In humans, intelligence emerges gradually, from early-acquired and possibly innate knowledge, through vision, embodied experience, social interaction, language, and years of learning. Yet already in infancy, humans exhibit early understanding of object perception, intuitive physics, and social interactions, often from relatively limited experience. In current machine learning systems, by contrast, learning typically relies on large-scale optimization over vast and diverse datasets, where many capabilities emerge together through training, leading to remarkable abilities in some domains while still struggling with tasks and intuitions that appear early in human development. This contrast raises fundamental questions about the nature of intelligence and learning: What can human development teach us about building more robust, flexible, and human-like AI systems? Recent work by the organizers points in this direction, showing how early visual experience, infant-like learning mechanisms, and cognitively inspired models of reasoning can inform the design of more robust, efficient, and generalizable AI systems. This workshop brings together researchers from cognitive development, neuroscience, psychology, and AI to examine intelligence through a developmental lens. In particular, the workshop will explore three central questions: What do human developmental trajectories reveal about the structure and emergence of intelligence? In what ways do current AI systems diverge from infant and child cognition? Can developmental insights lead to better AI systems, and how can such insights be incorporated into modern machine learning models?