Medical Education: Considerations for a Successful Integration of Learning with and Learning about AI

Abstract

Artificial intelligence (AI) with its diverse domains such as expert systems and machine learning already has multiple potential applications in medicine. Based on the latest developments in the multifaceted field of AI, it will play a pivotal role in medicine, with a high transformative potential in multiple areas, including drug development, diagnostics, patient care and monitoring. In the pharmaceutical industry AI is also rapidly gaining a crucial role. The introduction of innovative medicines requires profound background knowledge and the latest means of communication. This drives us to intensively engage with the topic of medical education, which is becoming more and more demanding due to the dynamic knowledge landscape, among other things, accelerated even more by digitalization and AI. Therefore, we argue for the incorporation of AI-based tools and methods in medical education, including personalized learning, diagnostic pathways, and data analysis, to prepare healthcare professionals for the evolving landscape of AI in medicine and support the fluency in dealing with AI by regular contact with various AI-based tools (Learning with AI). Understanding AI's vast potential and its caveats as well as gaining a basic knowledge of how AI works should be an important part of medical education to ensure that physicians can effectively and responsibly leverage AI-based systems in their daily practice and in scientific communication (Learning about AI).

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