Representation of intensivists' race/ethnicity, sex, and age by artificial intelligence: a cross-sectional study of two text-to-image models.

ABSTRACT:

Background

Integrating artificial intelligence (AI) into intensive care practices can enhance patient care by providing real-time predictions and aiding clinical decisions. However, biases in AI models can undermine diversity, equity, and inclusion (DEI) efforts, particularly in visual representations of healthcare professionals. This work aims to examine the demographic representation of two AI text-to-image models, Midjourney and ChatGPT DALL-E 2, and assess their accuracy in depicting the demographic characteristics of intensivists.

Methods

This cross-sectional study, conducted from May to July 2024, used demographic data from the USA workforce report (2022) and intensive care trainees (2021) to compare real-world intensivist demographics with images generated by two AI m

SUBMITTER: Gisselbaek M 

PROVIDER: S-EPMC11556211 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature