With the widespread use of AI systems in our everyday lives, it is important to factor fairness while designing these systems. In this work, we discuss fairness and bias related to healthcare AI: it’s impact, source, and actionable methods for evaluating and mitigating it. We demonstrate a hands-on fairness analysis of an algorithm used to predict healthcare cost, revealing fairness in model predictions across demographic groups.

Miguel Martinez is a Data Scientist at Optum Enterprise Analytics. Relied on as a tech lead in advancing AI healthcare initiatives, he is passionate about identifying and developing data science solutions for the benefit of organizations and people.