Abstract

Artificial intelligence (AI) deployed into healthcare settings is touted as an exciting approach for improving health equity. However, several issues need to be addressed before this could be achieved, including improving the collection and use of the social determinants of health data, enhancing data interoperability, closing the digital divide and conducting rigorous assessment and evaluation of AI applications to ensure that they achieve fair and equitable outcomes in real-world settings. Importantly, we should not neglect evidence-based strategies that will truly advance health equity, such as adequate housing, poverty reduction, accessible mental healthcare, food security and many other structural and social determinants of health.