Gender Representation of Health Care Professionals in Large Language Model-Generated Stories.

ABSTRACT:

Importance

With the growing use of large language models (LLMs) in education and health care settings, it is important to ensure that the information they generate is diverse and equitable, to avoid reinforcing or creating stereotypes that may influence the aspirations of upcoming generations.

Objective

To evaluate the gender representation of LLM-generated stories involving medical doctors, surgeons, and nurses and to investigate the association of varying personality and professional seniority descriptors with the gender proportions for these professions.

Design, setting, and participants

This is a cross-sectional simulation study of publicly accessible LLMs, accessed from December 2023 to January 2024. GPT-3.5-turbo and GPT-4 (OpenAI), Gemini-pro (Google), and Llam

SUBMITTER: Menz BD 

PROVIDER: S-EPMC11420694 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature