Gender Bias in Artificial Intelligence-Written Letters of Reference.

Journal: Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
PMID: 38716794

Abstract

OBJECTIVE: Letters of reference (LORs) play an important role in postgraduate residency applications. Human-written LORs have been shown to carry implicit gender bias, such as using more agentic versus communal words for men, and more frequent doubt-raisers and references to appearance and personal life for women. This can result in inequitable access to residency opportunities for women. Given the known gendered language often unconsciously inserted into human-written LORs, we sought to identify whether LORs generated by artificial intelligence exhibit gender bias.

Authors

  • Janice L Farlow
    Department of Otolaryngology-Head and Neck Surgery, Indiana University School of Medicine, Indianapolis, Indiana, USA.
  • Marianne Abouyared
    Department of Otolaryngology-Head and Neck Surgery, University of California Davis, Sacramento, California, USA.
  • Eleni M Rettig
    Department of Head and Neck Surgery, Brigham & Women's Hospital and Dana Farber Cancer Institute, Boston, Massachusetts, USA.
  • Alexandra Kejner
    Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina, USA.
  • Rusha Patel
    Department of Otolaryngology-Head and Neck Surgery, University of Oklahoma College of Medicine, Oklahoma City, Oklahoma, USA.
  • Heather A Edwards
    Department of Otolaryngolog-Head and Neck Surgery, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts, USA.

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