The Race + Data Science Lecture Series aims to celebrate and advance research in the areas of race and data, engineering, and computational science. With this series of events, our goal is to improve how we as data scientists and data-adjacent researchers speak about race. 


Guest Speaker

Brandeis Marshall, Professor of Computer Science, Computer and Information Sciences Department, Spelman College (currently on sabbatical leave)


Details & Recording

Wednesday, December 1 (11:00 AM – 12:00 PM ET) – Virtual


Chair & Moderator

Desmond Upton Patton, Associate Director of Diversity, Equity and Inclusion, The Data Science Institute, Columbia University. Patton is also Associate Professor of Social Work; Associate Dean of Curriculum Innovation and Academic Affairs; and Courtesy Appointment in Department of Sociology, Columbia University School of Social Work.


Abstract & Biography

Waking up to Marginalization in Data Education

Data education is increasingly becoming an integral part of many instructional structures, both informal and formal. Much of the attention has been on the application of AI principles and techniques. While AI is only one phase in the data ecosystem, we must embrace a fuller range of job roles that help manage AI algorithms and systems. Also, it’s important that we better understand the current state of the low participation and representation of minoritized groups that further stifles accessibility and inclusion efforts. In this talk, I’ll discuss the demographic disparities, bias creep and policy recommendations to curb and reduce this marginalization. 

Bio: Brandeis teaches, speaks and writes about the impact of data practices on technology and society. Her work contributes to the data engineering, data science, and data/computer science education fields. Through Dr. Marshall’s data education firm, she guides current tech workers building data equity skills. Her first book, Data Conscience: Algorithmic Siege on our Humanity, is expected to be released in mid-2022. It unearths the interlocking computational and civic implications of data on digital processes, structures and institutions.

Dr. Marshall holds a Ph.D. and Master of Science in Computer Science from Rensselaer Polytechnic Institute and a Bachelor of Science in Computer Science from the University of Rochester. She is on sabbatical leave from Spelman College, where she is a Full Professor of Computer Science.


The Race + Data Science Lecture Series is supported by funding from the MacArthur Foundation and New America.