Machine Learning Applications and Risks in Healthcare

This white paper discusses the implications of machine learning and artificial intelligence (AI) in the healthcare sector, addressing both its potential benefits and associated risks. It begins by detailing the historical context of AI, notably referring to Alan Turing's foundational work on the concept. The paper emphasizes the rapid evolution of AI applications, particularly the impact of large language models like ChatGPT, which have transformed how AI is utilized across various industries, including healthcare. The document outlines significant challenges in using generative AI within clinical contexts, particularly the accuracy of drug information. It highlights empirical studies that illustrate both the strengths and weaknesses of AI in clinical pharmacy practice. Moreover, the white paper addresses concerns surrounding AI's reliability, especially in high-stakes environments like healthcare, where incorrect outputs can have serious consequences. Additionally, it discusses the potential of AI to alleviate administrative burdens faced by healthcare providers and the necessity for robust regulations to ensure safe and effective implementation.