Wikipedia:Wiki Ed/Washington University in St. Louis/Signals Data and Equity (Fall 2023)

This course introduces the design of classification and estimation systems for equity, that is, with the goal of reducing the inequities of racism, sexism, xenophobia, ableism, and other systems of oppression. Systems which change the allocation of resources among people can increase inequity due to their inputs, the systems themselves, or how the systems interact in the context in which they are deployed. This course presents background in power and oppression, to help predict how new technological and societal systems might interact, and when they might confront or reinforce existing power systems. Measurement theory, the study of the mismatch between a system’s intended measure and the data it actually uses, is covered. Multiple example sensing and classification systems which operate on people (e.g., optical, audio, and text sensors) are covered by implementing algorithms and quantifying inequitable outputs.