Designing AI-resilient admissions interviews for health professions training in the age of generative AI.
rct · Level II
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- Record sourced from PubMed, PMID 42026111.
- Also identified by DOI 10.1038/s41746-026-02667-6 and PMC identifier 13316052.
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Abstract
Virtual interviews have now become standard practice in health professions training admissions following the COVID-19 pandemic, but the advent of generative AI technologies has raised concerns about the fairness and integrity of such practices. Admissions programs are responding with AI detection software, increased proctoring, and outright bans, all of which are difficult to enforce. A recent randomized controlled trial by Eva and colleagues examining Generative AI tool use among applicants to a medical school during virtual Multiple Mini‑Interviews (MMIs) suggests a different solution: good interview structure may be more resistant to AI advantage, and minor modifications can limit AI use without compromising reliability,authenticity or acceptability. Reframing generative AI as a design problem rather than a detection problem may also help align integrity, equity, and learning values.