AI and Human Decisions: Finding the Balance in a Data-Driven World

Abstract

Artificial Intelligence (AI) has emerged as a major transformative driver in healthcare decision-making, offering advanced solutions for diagnosis, treatment planning, personalized medicine, and drug development. AI-based technologies such as machine learning, deep learning, and predictive analytics have improved the accuracy, efficiency, and accessibility of healthcare services. AI-based diagnostic systems enhance the identification of diseases through the examination of intricate medical data, while AI-based clinical decision support systems assist healthcare professionals in the development of correct treatment plans. AI is also central in personalized medicine in the utilization of patient-specific genetic and clinical information to generate customized treatment regimens. In drug discovery, AI accelerates the identification of new drug candidates and optimizes pharmaceutical research processes, thereby saving time and resources. Nevertheless, regardless of its benefits, the application of AI in healthcare is affected by ethical and regulatory issues, such as the maintenance of patient data confidentiality, algorithmic bias, and transparency of AI-based decisions. Overcoming these is central to the facilitation of safe application of AI in healthcare environments. This paper discusses the applications, benefits, and challenges of AI in healthcare decision-making, with a focus on the significance of ethical guidelines and regulatory policies in realizing the potential of AI without causing harm.