Dear Applied Statistics Workshop Community, Our next meeting of the semester will be at *12:10 pm (EST) Wednesday, February 2*, where William La Cava <http://williamlacava.com> (Harvard University) presents "Unfairness in AI-based Clinical Decisions: Intersectional Approaches to Measurement and Mitigation." *Abstract* Clinical decision support systems increasingly rely on machine learning (ML) models to recommend courses of action. As a result, these systems have the potential to exacerbate inequities in healthcare allocation and disadvantage historically and contemporarily marginalized groups. To address this risk, fair ML algorithms have been proposed that minimize differences in model performance among patient groups. I will discuss some of these methods and the challenges to implementing them in practice. Two major challenges are to measure and mitigate these differences when we consider grouping patients by intersections of demographic variables such as age, race, ethnicity, sex, and socio-economic status. *Where:* CGIS Knafel Building, Room K354 (See this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When:* Wednesday, February 2 at 12:10 - 1:30 pm. (Bagged lunches available for pick-up at CGIS K354 *11:30 - 11:45 am*, for the participants who responded to our previous survey. The CGIS cafe on the first floor has been designated as an eating area, and participants may also use outdoor spaces for lunch. Please be present at K354 by 12:10 pm for the presentations.) *Zoom link*: https://harvard.zoom.us/j/97004196610?pwd=eGFydkF5RDRjUlk5RVcyTjV6OStUQT09 (For the participants who cannot join the session physically.) *Schedule of the workshop*: https://projects.iq.harvard.edu/applied .stats.workshop-gov3009 Looking forward to seeing you all on Wednesday! Best, Sooahn