Ethical considerations in implementing generative AI for healthcare supply chain optimization: A cross-country analysis across India, the United Kingdom, and the United States of America

Abstract

This review paper critically examines the ethical considerations involved in implementing generative Artificial Intelligence (AI) in healthcare supply chain optimization across three distinct regions: India, the United Kingdom, and the United States of America. The study synthesizes findings from various case studies and academic research to highlight both common and unique ethical challenges faced in these countries. Key themes such as data privacy, algorithmic transparency, and equitable access to AI-driven healthcare solutions are explored, alongside the unique socio-cultural, legal, and regulatory challenges specific to each region. The paper proposes a set of best practices for incorporating ethical considerations into the deployment of generative AI in healthcare. These include the development of inclusive ethical frameworks, regular ethical audits, comprehensive training and education programs, public engagement initiatives, and interdisciplinary collaboration. The paper also delves into future research directions and policy development, emphasizing the need to address healthcare disparities, adapt legal and regulatory frameworks, enhance generative AI explainability, and evaluate long-term outcomes.The study concludes by underscoring the importance of ethical design and deployment of generative AI systems in healthcare, advocating for a balanced approach that aligns technological advancements with ethical standards and global healthcare needs. This comprehensive review aims to contribute to the discourse on ethical generative AI implementation, offering insights and recommendations for policymakers, healthcare professionals, and generative AI developers to foster responsible and beneficial use of generative AI in healthcare globally.