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UVA Data Points - A Conversation with Virginia Eubanks

A Conversation with Virginia Eubanks

02/01/23 • 70 min

UVA Data Points

This episode features a conversation between Lane Rasberry, Wikimedia-in-Residence at the University of Virginia School of Data Science, and Virginia Eubanks, author, journalist, and associate professor of political science at the University at Albany.

The conversation was recorded in 2019 but the topics are still relevant today. Eubanks looks toward the future, warning of the unintended—or at times intended—consequences of emerging technologies. The discussion focuses on the effects of algorithmic automation, as well as the practice, policies, and implementation of these algorithms. Although she critiques the tech world, Eubanks also provides many reasons for optimism.

Virginia Eubanks authored the 2018 book Automating Inequality, which is a detailed investigation into data-based discrimination. She is also the author of Digital Dead End: Fighting for Social Justice in the Information Age and the co-editor, with Alethia Jones, of Ain’t Gonna Let Nobody Turn Me Around: Forty Years of Movement Building with Barbara Smith. She also writes for various outlets, including the Guardian, American Scientist, and the New York Times. Recently, Virginia began the PTSD Bookclub, an ongoing project that explores books about trauma and its aftermath. You can find this project and Virginia Eubank’s other projects at virginia-eubanks.com.

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This episode features a conversation between Lane Rasberry, Wikimedia-in-Residence at the University of Virginia School of Data Science, and Virginia Eubanks, author, journalist, and associate professor of political science at the University at Albany.

The conversation was recorded in 2019 but the topics are still relevant today. Eubanks looks toward the future, warning of the unintended—or at times intended—consequences of emerging technologies. The discussion focuses on the effects of algorithmic automation, as well as the practice, policies, and implementation of these algorithms. Although she critiques the tech world, Eubanks also provides many reasons for optimism.

Virginia Eubanks authored the 2018 book Automating Inequality, which is a detailed investigation into data-based discrimination. She is also the author of Digital Dead End: Fighting for Social Justice in the Information Age and the co-editor, with Alethia Jones, of Ain’t Gonna Let Nobody Turn Me Around: Forty Years of Movement Building with Barbara Smith. She also writes for various outlets, including the Guardian, American Scientist, and the New York Times. Recently, Virginia began the PTSD Bookclub, an ongoing project that explores books about trauma and its aftermath. You can find this project and Virginia Eubank’s other projects at virginia-eubanks.com.

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undefined - The Future of Academic Data Science

The Future of Academic Data Science

In this episode we’re bringing you a conversation on the future of academic data science recorded live at UVA Data Science’s Datapalooza 2022 event

Datapalooza is a flagship event for the School of Data Science. It’s typically held each year in November and features presentations by researchers here at UVA, as well as friends and collaborators of the School of Data Science.

In this episode we’re featuring a panel discussion between:

  • Doug Hague, the Executive Director at UNC-Charlotte’s School of Data Science
  • H.V. Jagadish, Director of the Michigan Institute for Data Science at the University of Michigan
  • Phil Bourne, Dean of the UVA School of Data Science
  • And Micaela Parker, Founder and Executive Director of the Academic Data Science Alliance. Micaela also serves as the moderator for this panel discussion.

Links:

Future of Academic Data Science video recording

Michigan Institue of Data Science

UNC Charlottes School of Data Science

UVA School of Data Science

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undefined - Brain Science is Data Science

Brain Science is Data Science

This episode explores the intersection of neuroscience and data science with three experts in the field, Drs. John Darrell van Horn, Tanya Evans, and Teague Henry. As we know, the brain is complicated. People have been charting paths through the brain for decades, making breakthroughs and discoveries that have changed the world. In recent years though, new methodologies in brain research have made significant impacts. Advances in computing power, as well as techniques like machine learning, neural networks, and computer vision, have allowed researchers to ask questions and make discoveries that were not possible even ten years ago. Given these new approaches to studying the world’s most complicated organ, one could say that brain science is data science. Our guests make a compelling case.

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