Work

Guiding principles for the responsible development of artificial intelligence tools for healthcare

Year: 2023

Type: article

Abstract: Several principles have been proposed to improve use of artificial intelligence (AI) in healthcare, but the need for AI to improve longstanding healthcare challenges has not been sufficiently emphasized. We propose that AI should be designed to alleviate health disparities, report clinically meaningful outcomes, reduce overdiagnosis and overtreatment, have high healthcare value, consider biographical drivers of health, be easily tailored to the local population, promote a learning healthcare system, and facilitate shared decision-making. These principles are illustrated by examples from breast cancer research and we provide questions that can be used by AI developers when applying each principle to their work.

Source: Communications Medicine

DOI: 10.1038/s43856-023-00279-9

Authors: Kimberly Badal, Carmen M. Lee, Laura J. Esserman

Institutions: University of California, San Francisco, UCSF Helen Diller Family Comprehensive Cancer Center, Alameda Health System, Highland Hospital

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDGs: Good health and well-being, Reduced inequalities

Open Access status: gold

Estimated APC paid: $3,390