Building Diversity, Equity, and Inclusion Within Radiology Artificial Intelligence: Representation Matters, From Data to the Workforce.

TitleBuilding Diversity, Equity, and Inclusion Within Radiology Artificial Intelligence: Representation Matters, From Data to the Workforce.
Publication TypeJournal Article
Year of Publication2023
AuthorsDoo FX, McGinty GB
JournalJ Am Coll Radiol
Volume20
Issue9
Pagination852-856
Date Published2023 Sep
ISSN1558-349X
Abstract

Diversity, equity, and inclusion (DEI) is both a critical ingredient and moral imperative in shaping the future of radiology artificial intelligence (AI) for improved patient care, from design to deployment. At the design level: Potential biases and discrimination within data sets results in inaccurate radiology AI models, and there is an urgent need to purposefully embed DEI principles throughout the AI development and implementation process. At the deployment level: Diverse representation in radiology AI leadership, research, and career development is necessary to avoid worsening structural and historical health inequities. To create an inclusive and equitable AI-enabled future in healthcare, a DEI radiology AI leadership training program may be needed to cultivate a diverse and sustainable pipeline of leaders in the field.

DOI10.1016/j.jacr.2023.06.014
Alternate JournalJ Am Coll Radiol
PubMed ID37453602

Weill Cornell Medicine
Department of Radiology
525 East 68th Street New York, NY 10065