All Times EDT
Addressing Bias, Equity, and Anti-Racism as a Technical Contributor (309922)*Emily Catherine Hadley, RTI International
Keywords: Equity, data, bias, anti-racism
As statisticians and data scientists, we collect data, store data, transform data, visualize data, and ultimately impact how data are used. With this responsibility, it is imperative that we understand the ways in which data and algorithms have been used to perpetuate racism and bias, and work to eliminate racist and biased decisions and algorithms in our own work. In this session, explore the landscape of bias, equity, and anti-racism in statistics, data science, and machine learning. Discuss relevant examples from recent literature and consider questions to ask and techniques to use for addressing bias, equity, and anti-racism in data as a technical contributor.