Abstract
Advancing the study of primate cognition requires methods that preserve ecological validity while enabling the experimental control typical of laboratory research. We introduce CapuchinAI, a field-deployable touchscreen system that integrates real-time facial recognition with automated cognitive testing, providing a novel methodological framework for studying cognition in wild primates. Our approach combines a high-performing (>97% accuracy) YOLOv7-based facial recognition model (Multiple Capuchins v1.0) with a portable Raspberry Pi-driven touchscreen-reward apparatus designed for automated operation in natural habitats. The system detects approaching capuchins, initiates video recording, presents touchscreen stimuli, and dispenses food rewards contingent on task performance. During a two-week presentation to two habituated groups of wild white-faced capuchins (Cebus imitator) at the Taboga Forest Reserve, 16 individuals voluntarily interacted with the apparatus, 10 learned to trigger rewards, and 8 formed and retained robust screen-reward associations. The rapid habituation and learning rates demonstrate the feasibility of deploying AI-mediated cognitive experiments in the wild. CapuchinAI addresses several long-standing challenges in field cognition research by enabling: (1) autonomous, individualized task administration without researcher intervention; (2) standardized, repeatable trials across individuals and sessions; (3) scalable deployment across groups and sites; and (4) parallel data collection on behavior, identity, and performance. This methodology provides a blueprint for integrating machine learning, touchscreen testing, and automated reward delivery to study within- and between-individual cognitive variation under natural conditions. CapuchinAI represents a significant step toward long-term comparative research on primate cognition by making laboratory experimental paradigms accessible in the wild, bridging the gap between lab and field.