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Accepted for/Published in: JMIR AI

Date Submitted: Jan 30, 2024
Date Accepted: May 17, 2025

The final, peer-reviewed published version of this preprint can be found here:

Generative AI in Medicine: Pioneering Progress or Perpetuating Historical Inaccuracies? Cross-Sectional Study Evaluating Implicit Bias

Sutera P, Bhatia R, Lin T, Chang L, Brown A, Jagsi R

Generative AI in Medicine: Pioneering Progress or Perpetuating Historical Inaccuracies? Cross-Sectional Study Evaluating Implicit Bias

JMIR AI 2025;4:e56891

DOI: 10.2196/56891

PMID: 40605830

PMCID: 12223688

Generative AI in Medicine: Pioneering Progress or Perpetuating Historical Inequities?

  • Philip Sutera; 
  • Rohini Bhatia; 
  • Timothy Lin; 
  • Leslie Chang; 
  • Andrea Brown; 
  • Reshma Jagsi

ABSTRACT

In a pilot experiment, we utilized AI to generate 100 photographs of physicians in 19 medical subspecialties and compared these photographs to the existing and incoming medical specialty workforce. Our work demonstrates that generative AI has a tendency to under represent women in common specialties, and thus the utilization of this tool in the future must be viewed with caution and a lens of known historical bias.


 Citation

Please cite as:

Sutera P, Bhatia R, Lin T, Chang L, Brown A, Jagsi R

Generative AI in Medicine: Pioneering Progress or Perpetuating Historical Inaccuracies? Cross-Sectional Study Evaluating Implicit Bias

JMIR AI 2025;4:e56891

DOI: 10.2196/56891

PMID: 40605830

PMCID: 12223688

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