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AI-Augmented Redistribution: Human-AI Collaboration to Prevent Waste and Feed Communities

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  • Bharat Kumar Bharatha

    (Independent Researcher, USA)

Abstract

This article evaluates the new variant of paradigm shift in the human-AI partnership in food redistribution systems to solve the two interdependent issues of food waste and food insecurity. Manual redistribution practices are becoming unsuitable to such challenges based on their magnitude and complexity. The use of artificial intelligence in cooperation with human skills is not merely beneficial but essential, as neither technology nor human effort alone can adequately address the scale, speed, and ethical complexities inherent in modern food redistribution. While AI provides the computational power to process millions of inventory points and logistics variables simultaneously, human oversight remains irreplaceable for ethical decision-making, quality assurance, and community relationship management. The article examines the situation of current redistribution, outlines the technical aspects of human-AI collaborative technology, considers the tactical distribution of roles between technological and human factors, and outlines major implementation issues. Multi-layered technology stack with robotic process automation, machine learning, APIs, logistics platforms, and blockchain technologies allows new levels of efficiency and scale. Moving forward, the article suggests a model of co-orchestration in which AI agents and human employees act as joint administrators of multifaceted redistribution ecosystems with technologies like smart contracts, intelligent packaging systems, and federated learning increasing potential without losing critical human control. The advantage of such a balanced course of action is that the strong and weak aspects of technology and humanity are utilized to establish more equal and sustainable food distribution networks.

Suggested Citation

  • Bharat Kumar Bharatha, 2025. "AI-Augmented Redistribution: Human-AI Collaboration to Prevent Waste and Feed Communities," Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 7(10), pages 120-127, September.
  • Handle: RePEc:alk:jcsts0:v:7:y:2025:i:10:id:11072
    DOI: 10.32996/jcsts.2025.7.10.12
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