Ethical Challenges of Artificial Intelligence in Medicine

Abstract

Artificial intelligence (AI) and machine learning (ML) have become critical components in the transformation of healthcare. They offer enhanced diagnostic accuracy, personalized treatment plans, and support for clinical decision-making. However, with these advancements come significant ethical challenges, including concerns around transparency, bias, data privacy, and the potential displacement of healthcare professionals. This review delves into these ethical concerns, issues of transparency, data privacy, bias, and the moral responsibility of decision-making with a particular focus on the role of AI in new drug/genetic treatment discovery, exploring how AI models are employed in protein, RNA, and DNA structural prediction to accelerate drug development. Addressing these challenges is crucial for ensuring that AI is used responsibly, benefiting patients while maintaining trust in the healthcare system.