The Central Illinois Chapter of the American Statistical Association is inviting you to a virtual seminar on Friday, January 24, at 12:00 pm CST.
Speaker: Dr. David Corliss
Title: Designing Against Bias: Identifying and Mitigating Bias in Machine Learning and AI
Abstract: Bias in machine learning algorithms is one of the most important ethical and operational issues in statistical practice today. This presentation describes common sources of bias and how to develop study designs to measure and minimize it. Analysis of disparate impact is used to quantify bias in existing and new applications. Also, a comparison algorithm can be developed that is designed to be fully transparent and without features subject to bias. Comparison to this bias-minimized model can identify areas as bias in other algorithms. These design strategies are described in detail with practical examples in R.
Bio: David J Corliss, PhD is the Principal Data Scientist at Grafham Analytics. His work in best practices for ethical machine learning and AI includes teaching a traveling course from the American Statistical Association on ethical challenges in data and analytics, serving on the steering committee of the Statistics section of the American Association for the Advancement of Science, and writing a column on Data for Good in Amstat News. This January he started a three-year term on the board of the American Statistical Association as a representative from the Council of Chapters. Dr. Corliss is the founder of Peace-Work, a volunteer cooperative of statisticians, data scientists and other researchers applying analytics in issue-driven advocacy.
Join Zoom Meeting
https://wiu.zoom.us/j/95424706336?pwd=bDTIlnOM1bamnePveAWKSWNQblgPfe.1
Meeting ID: 954 2470 6336
Passcode: 173406
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Anna Valeva, PhD
Associate Professor
Western Illinois University
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