AI-Driven STEM Education for Public Health in Sustainable Agriculture

As the global population approaches 10 billion by 2050, sustainable agriculture faces unprecedented pressure to ensure food security while mitigating climate change impacts, with artificial intelligence (AI) emerging as a pivotal tool for precision farming. This review synthesizes recent global evidence on how AI-driven STEM education equips future generations for sustainable practices, directly linking to public health outcomes like reduced malnutrition and environmental risks. AI applications, including simulations for crop management and IoT for resource optimization, enhance efficiency, cutting water consumption by 40–60% and pesticides by 20–30%, thereby improving crop quality and public health. STEM education incorporates these technologies through curricula emphasizing data analytics and robotics, fostering innovation in low-resource regions like sub-Saharan Africa and South Asia. Public health benefits include better nutrition from AI-optimized crops and lower disease exposure from reduced chemicals. Challenges such as data scarcity and ethical biases are addressed through hybrid models and training programs. Future directions emphasize explainable AI and federated learning for equitable access. These insights inform educators and policymakers on leveraging AI-STEM synergy for healthier, sustainable food systems.