AI literacy among healthcare professionals and students in the Americas

Abstract

Artificial Intelligence (AI) applications in health care continue to grow exponentially, and AI-tools such as machine learning (ML), natural language processing (NLP), and generative pre-trained transformers (GPT) continue to transform medical education. The adoption of AI in medical education however remains geographically varied, with studies illustrating a relatively lower research output on medical AI literacy in Latin America (LATAM) countries compared to North America. AI-applications offer significant potential to broaden access to medical education and facilitate evidence-based support with clinical decision-making, particularly in low- and middle-income countries (LMICs). Enhancing AI literacy in such settings is of paramount importance - successful integration may alleviate historical disparities, while improper implementation may deepen regional inequities in medical education and health care. In this viewpoint article, we illustrate the current state of AI-based medical education across the Americas, highlight challenges in implementation, and offer collaborative, equitable, and regionally tailored strategies to enhance medical AI literacy among health care professionals and students.

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