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In April 2021, the U.S. Centers for Medicare and Medicaid Services announced the winner and runner-up of the CMS Artificial Intelligence Health Outcomes Challenge, the largest-ever prize competition for innovators to demonstrate how AI solutions can predict patient health events. The two-year competition was described as “an exciting example of how public/private partnerships can drive innovation.” This panel will explore how the winner and runner-up in the AI Challenge approached health equity by measuring and mitigating algorithmic bias. The panelists will discuss the current and future state of algorithmic bias in applications using healthcare claims data, debating topics such as: 1) how to effectively identify the sources of bias in AI algorithms—including data quality and representativeness, 2) the difference between bias and fairness, 3) the value of scoring systems for quantifying bias, and 4) practical implications of applying predictive models in healthcare compared to other settings. Ample time will be provided for audience questions and discussion.