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CapuchinAI 1.0: Development of a Machine Learning-Based Touchscreen Paradigm to Test Cognition in Wild Capuchins
Federico Sánchez Vargas1, Sai Rakshith Potluri2,3, Jacob Abernethy2
1Department of Anthropology, Emory University, Atlanta, Georgia, USA.
American Journal of Primatology
|July 28, 2026
Summary
We developed CapuchinAI, an AI-powered field system for studying wild primate cognition. This automated touchscreen technology enables real-time cognitive experiments in natural habitats, demonstrating rapid learning in capuchins.
Area of Science:
- Primate cognition
- Artificial intelligence in behavioral science
- Field methodology
Background:
- Studying primate cognition requires balancing ecological validity with laboratory-level experimental control.
- Existing field methods often lack the precision for detailed cognitive assessments.
- There is a need for automated, non-invasive tools to study wild animal cognition.
Purpose of the Study:
- To introduce CapuchinAI v1.0, a novel field-deployable system for automated cognitive testing in wild primates.
- To demonstrate the feasibility of integrating AI-driven species recognition and touchscreen interfaces for cognitive research.
- To bridge the gap between laboratory-based cognitive studies and ecologically valid field observations.
Main Methods:
- Developed CapuchinAI, combining a YOLOv7-based facial recognition model (MultipleCapuchins) with a Raspberry Pi touchscreen-reward apparatus.
- Deployed the system in the Taboga Forest Reserve for automated cognitive testing with wild white-faced capuchins (Cebus imitator).
- The system automatically detects capuchins, initiates recording, presents stimuli, and dispenses rewards upon interaction.
Main Results:
- 16 wild capuchins voluntarily interacted with the CapuchinAI apparatus over a 2-week period.
- 10 individuals successfully triggered food rewards through interaction.
- 8 capuchins rapidly formed and maintained robust associations between screen interaction and reward.
Conclusions:
- CapuchinAI demonstrates the feasibility of AI-mediated cognitive experiments in natural primate habitats.
- The system facilitates autonomous, standardized, and scalable cognitive testing in the wild.
- This methodology advances comparative research on primate cognition by enabling study under natural conditions.
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