Artificial intelligence and machine learning tools in residency recruitment have the potential to reduce bias, but educators must actively mitigate unintentional biases that may result from AI adoption.
Artificial intelligence (AI) has the potential to revolutionize neurology education, 1 including in residency recruitment.Machine learning (ML) is a growing branch of AI that focuses on identifying patterns in large data sets, at times allowing machines to later self-learn and adapt over time; innovators are already integrating ML into decision-support tools for residency application review. 2 Natural language processing (NLP), another subfield of AI that seeks to understand and process human language, may be integrated within ML to enable machines to process unstructured text, such as personal statements and letters of recommendation.As ML and NLP use expands in application review, neurology educators must understand how AI-derived tools may affect equity in the recruitment process.Programs that choose to integrate AI in resident selection should harness the potential for AI to reduce bias and mitigate unintentional biases that may result from AI adoption (Figure).
Gottlieb‐Smith et al. (Fri,) conducted a editorial in Neurology residency recruitment. Artificial Intelligence (AI) was evaluated. Artificial intelligence and machine learning tools in residency recruitment have the potential to reduce bias, but educators must actively mitigate unintentional biases that may result from AI adoption.