Ethical and Social Implications of Generative AI in Supply Chain Management

EasyChair Preprint 13085

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

Keyphrases: Generative AI, bias, ethical implications, fairness, management, social implications, supply chain

@booklet{EasyChair:13085,
  author    = {Dylan Stilinski and Lucas Doris and Louis Frank},
  title     = {Ethical and Social Implications of Generative AI in Supply Chain Management},
  howpublished = {EasyChair Preprint 13085},
  year      = {EasyChair, 2024}}