07 Jun Bias Checklist – JAMIA
As a user exploring deployment of healthcare AI, a key challenge has been the lack of a comprehensive assessment for measuring bias within your solution. Further complicating matters; most scientific papers focus on one or two aspects of bias while meta-reviews or industry tool-kits simply surveil or summarize existing quantitative measures.
In a first-of-its-kind research paper by JAMIA (a leading informatics journal) our very own Suchi Saria brings together a team of experts in health disparities, health services, machine learning and informatics, providing a rare, end-to-end perspective of bias.
If you are exploring deployment of AI to improve patient outcomes, lower readmissions and decrease alert fatigue, this checklist provides a solid foundation for identifying and overcoming sources of bias.