Advancing health equity with artificial intelligence

Journal of Public Health Policy
Volume 42, issue 4, December 2021
https://link.springer.com/journal/41271/volumes-and-issues/42-4

 

Advancing health equity with artificial intelligence
Authors – Nicole M. Thomasian, Carsten Eickhoff
Eli Y. Adashi
Content type: Viewpoint
Published: 22 November 2021
Pages: 602 – 611
Abstract
Population and public health are in the midst of an artificial intelligence revolution capable of radically altering existing models of care delivery and practice. Just as AI seeks to mirror human cognition through its data-driven analytics, it can also reflect the biases present in our collective conscience. In this Viewpoint, we use past and counterfactual examples to illustrate the sequelae of unmitigated bias in healthcare artificial intelligence. Past examples indicate that if the benefits of emerging AI technologies are to be realized, consensus around the regulation of algorithmic bias at the policy level is needed to ensure their ethical integration into the health system. This paper puts forth regulatory strategies for uprooting bias in healthcare AI that can inform ongoing efforts to establish a framework for federal oversight. We highlight three overarching oversight principles in bias mitigation that maps to each phase of the algorithm life cycle.