Bridging the mentorship divide: how large language models could reshape medical workforce equity
Abstract
Mentorship in predictive large language models (LLMs) presents both opportunities and risks of inequity if these systems are not designed with care. Mentorship quietly shapes medical careers, yet opportunities for it remain unequal. LLMs can analyze student writing and may reveal potential that exams overlook. This predictive capacity could inform fairer mentorship and direct support to students who need it most, helping build a more equitable medical workforce.
Fields of Study & Subjects
Diversity and Career in Medicine
Artificial Intelligence in Healthcare and Education
Social Media in Health Education
Publication details
- Journal / source
- npj Digital Medicine
- Publisher
- Springer Science and Business Media LLC
- Volume
- 9
- Issue
- 1
- Pages
- 29–29
- Publication date
- 9 January 2026
- Language
- EN