AI in agriculture is poised to revolutionize the sector by identifying hidden patterns in crops and climate, enhancing resilience and productivity. The concept of “responsible, application-driven AI” (RAD-AI), co-designed with farmers, is crucial for building trust in technology. As illustrated by Dr. Sarah Hartman’s research post-Kakhovka Dam disaster, AI can effectively monitor agricultural health using satellite imagery, revealing areas of both collapse and recovery. This approach emphasizes the importance of quality data for accurate AI modeling and the need for co-design with local communities to cater to diverse agricultural contexts. Innovations such as AI-driven drones for livestock management and advanced weather forecasting tools highlight AI’s versatility. However, they also come with challenges and risks, emphasizing that AI should not be seen as a panacea. Instead, a focus on responsible design and data integrity is essential for maximizing its potential in supporting sustainable agriculture by 2050.
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