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Artificial Intelligence in Food Bank and Pantry Services: A Systematic Review
Yuanyuan Yang1, Ruopeng An2, Cao Fang1
1Brown School, Washington University in St. Louis, St. Louis, MO 63130, USA.
Nutrients
|May 14, 2025
Summary
Artificial intelligence (AI) shows promise for improving food bank operations, but current research is limited. Further studies are needed to explore AI
Area of Science:
- Food security and public health
- Operations research and management
- Artificial intelligence applications
Background:
- Food banks and pantries are vital for food security, yet face operational challenges like donation variability and supply-demand mismatches.
- Artificial intelligence (AI) is increasingly adopted across industries, suggesting potential for addressing complex operational issues in food assistance programs.
Purpose of the Study:
- To systematically review empirical evidence on the application of artificial intelligence (AI) in food bank and pantry services.
- To identify current trends, methodologies, and limitations of AI in enhancing food bank operations.
Main Methods:
- Systematic literature review adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
- Comprehensive search across 11 electronic bibliographic databases up to April 15, 2025.
- Inclusion of peer-reviewed papers focusing on AI applications in food banks and pantries.
Main Results:
- Five peer-reviewed papers (2015-2024) were identified, predominantly using structured data machine learning algorithms (e.g., neural networks, random forests).
- One study utilized text-based topic modeling.
- Research focused on food donation processes (3 studies) and food collection/distribution (2 studies).
Conclusions:
- AI demonstrates emerging potential to enhance food bank and pantry operations.
- Significant limitations exist, including a scarcity of studies, limited geographic scope, and methodological concerns (data representativeness, statistical power).
- Ethical considerations (AI bias, fairness) and policy implications require deeper investigation in future research.
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