Randomized trial demonstrates improved volunteer engagement and operational efficiency in food rescue operations, indicating effective AI utilization.
We present and deploy an AI-driven volunteer engagement system for a large food rescue organization that combines optimization and machine learning to improve how volunteers are notified about food rescue opportunities. We develop both an optimized global notification policy and a rescue-specific recommender system with online planning, then validate the approach through real-world deployment and a randomized controlled trial. Our results demonstrate substantial improvements in volunteer engagement, rescue claim rates, and operational efficiency while reducing unnecessary notifications.
No takes yet. Share an insight, caveat, or question.
Shi et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: