Generative artificial intelligence in postgraduate medical education

Generative artificial intelligence is swiftly revolutionizing multiple areas, including healthcare and education. This research examines the possible advantages and hazards of generative artificial intelligence in graduate medical education. We examine the current literature and offer insights on the potential effects of generative artificial intelligence on graduate medical education, highlighting five principal areas of opportunity: reduction of electronic health record workload, clinical simulation, personalized education, research and analytics assistance, and clinical decision support. We subsequently examine critical hazards, such as inaccuracies and excessive dependence on artificial intelligence-generated information, threats to authenticity and academic integrity, potential biases in artificial intelligence outputs, and privacy issues. As generative artificial intelligence technology advances, it is poised to play a significant role in the future of graduate medical education; nevertheless, its integration must be informed by a comprehensive understanding of its advantages and constraints.