The Adaptive Human-AI Synergy in Logistics (AHASL) Theory
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, AIDownloads
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- 2024-11-16 (3)
- 2024-11-16 (2)
- 2024-11-16 (1)
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Copyright (c) 2024 Rachid Ejjami
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt the material for non-commercial purposes, as long as proper credit is given to the author and any changes made are indicated.