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Home > CIIMA > Vol. 22 (2024) > Iss. 1

 

Communications of the IIMA

Abstract

As organizations increasingly adopt artificial intelligence (AI) technologies to optimize their supply chain operations, they face a growing set of ethical challenges that demand careful consideration. This study explores the key ethical dilemmas and potential solutions in implementing AI within the supply chain context, drawing insights from in-depth interviews with a diverse group of experts. The thematic analysis of the interview data revealed four primary ethical dilemmas: algorithmic bias and discrimination, lack of transparency and explainability, privacy and data ethics issues, and the socioeconomic impacts of AI-driven automation. To address the dilemmas, this study identified various mitigation strategies, including techniques for bias detection and correction, methods for improving the interpretability of AI-driven decisions, comprehensive data governance frameworks, and approaches to responsible automation that prioritize human-AI collaboration. The findings of this research are grounded in various philosophical principles, such as fairness and distributive justice, and the ethical treatment of workers in the face of technological change.

By contextualizing the practical challenges within these broader philosophical considerations, the study provides a holistic understanding of the ethical implications of AI adoption in supply chain management.

The proposed ethical AI governance framework for supply chain organizations offers a systematic approach to navigating the complex terrain of responsible innovation, fostering a culture of ethical decision-making, and ensuring the long-term sustainability of AI-powered supply chain operations.

This research contributes to the growing body of literature on the ethical dimensions of emerging technologies and their implementation within operational settings.

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