The Adaptive Human-AI Synergy in Logistics (AHASL) Theory

Authors

  • Dr. Rachid Ejjami Managing Director and Editor-in-Chief of the Journal of Next-Generation Research 5.0, and graduate of École des Ponts Business School, École Nationale des Ponts et Chaussées - Institut Polytechnique de Paris.

Abstract

This paper introduces the Adaptive Human-AI Synergy in Logistics (AHASL) theory, which focuses on integrating artificial intelligence (AI) into logistics and supply chain management. The study takes a qualitative approach, using interviews, observations, and reflexive journaling, and finds that while AI significantly improves operational efficiency and decision-making, human oversight is still required to address AI's limitations, such as bias, lack of transparency, and potential skill erosion. The AHASL model prioritizes Full-Spectrum Explainability (FSE) and a Bias Mitigation Framework (BMF) to ensure that AI-driven decisions are transparent and equitable while simultaneously arguing for retaining human expertise to retain adaptability and resilience in logistical operations. The study's findings emphasize the significance of balanced human-AI collaboration. However, they also call for more research into the long-term effects, scalability, and ethical implications of AI integration in logistics.

Keywords:

Human-AI synergy, Logistics, AI transparency, Bias mitigation, AI

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Published

2024-11-16 — Updated on 2024-11-16

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How to Cite

Ejjami, R. (2024). The Adaptive Human-AI Synergy in Logistics (AHASL) Theory. Journal of Next-Generation Research 5.0, 1(1). https://doi.org/10.70792/jngr5.0.v1i1.12

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