Ethical and Social Implications of Generative AI in Supply Chain Management

EasyChair Preprint 12926

Abstract

The integration of generative artificial intelligence (AI) into supply chain management brings forth a myriad of ethical considerations, privacy concerns, and socio-economic impacts that warrant careful examination. This abstract delves into the multifaceted dimensions of these implications, particularly focusing on bias, fairness, accountability, and the future of work in AI-driven supply chain environments.

Generative AI, with its ability to synthesize data and simulate scenarios, offers unparalleled capabilities in optimizing supply chain operations. However, the reliance on AI algorithms raises concerns regarding algorithmic bias and fairness. Biases inherent in training data or algorithmic decision-making processes can perpetuate inequalities and discrimination, affecting various stakeholders across the supply chain ecosystem. Addressing these biases and ensuring fairness in AI-driven decision-making processes are imperative for upholding ethical standards and fostering inclusivity.

Privacy concerns also loom large in AI-driven supply chains, particularly with the collection and analysis of vast amounts of sensitive data. The aggregation of personal data from various sources, including customer preferences, employee records, and supplier information, raises concerns about data privacy and protection. Safeguarding individuals' privacy rights and ensuring compliance with data protection regulations are paramount to maintaining trust and ethical integrity in AI-driven supply chain environments.

Keyphrases: Accountability, Generative AI, Socioeconomic impacts, Supply Chain Management, algorithmic decision-making, bias, ethical implications, fairness, privacy concerns, social implications

@booklet{EasyChair:12926,
  author    = {Dylan Stilinski and Lucas Doris and Louis Frank},
  title     = {Ethical and Social Implications of Generative AI in Supply Chain Management},
  howpublished = {EasyChair Preprint 12926},
  year      = {EasyChair, 2024}}