Algorithmic bias discussion to highlight Mathematics and Statistics Awareness Month series

Dr. Maria De-Arteaga, Assistant Professor, Information, Risk and Operations Management Department, University of Texas at Austin

Maria De-Arteaga will present "Sources and Consequences of Algorithmic Bias" as part of the Texas State University Department of Mathematics' annual Mathematics and Statistics Awareness Month Series on April 8.

De-Arteaga's presentation, which is free and open to the public, will be delivered 3-4 p.m. via Zoom. A panel discussion with representation from the Department of Computer Science and the Department of Philosophy will follow at 4-5 p.m. 

The Zoom link and additional information may be found at https://msam.wp.txstate.edu/.

Machine learning (ML) is increasingly being used to assist experts in consequential domains. In her talk, De-Arteaga will characterize risks of algorithmic bias and provide an overview of its sources and consequences. She will present findings from her research across domains, including gender bias in automated recruiting and the effect of differential victim crime reporting on predictive policing systems. She will conclude with takeaways for the design and deployment of responsible ML.

De-Arteaga is an assistant professor at the Information, Risk and Operations Management Department at the University of Texas at Austin, where she is also a core faculty member in the Machine Learning Laboratory and an affiliated faculty of Good Systems.

The panel discussion will feature Vaughn Baltzly, assistant professor in the Department of Philosophy, Sami Alsheikh, engineer-in-residence in the Department of Computer Science and software engineer at Meta, and Ted Lehr, senior lecturer in the Department of Computer Science. Some of the issues the discussion will cover include defining what unwanted bias is, when it is unwanted and how to detect or prevent it, how human interaction with algorithms adds or detracts from bias, and the ethics of using generated algorithms not fully understood.

The event is supported by the Department of Mathematics, Department of Computer Science, Department of Philosophy and Mathworks at Texas State.