2020 Ethics of Big Data Symposium
Virtual Symposium: Race, Representation & Justice
The 5th Annual Marquette "Ethics of Big Data Symposium" will take place virtually on Friday, October 9, 2020.
As we look at the events of 2020, we cannot ignore how issues of race, representation, and justice intersect with the growing reliance on data, algorithims, and computational approaches in nearly all aspects of our lives. Big data increasingly impacts how information flows across networks, how law enforcement and the criminal justice system operate in our communities, how individuals and communities are made visible (or invisible), how public & social services are dispersed, and, most fundamentally, how justice might be possible in our society.
The 5th Annual Marquette "Ethics of Big Data Symposium" explores how data intersects with critical issues race, representation, and justice in and across our communities. Please join us for this important discussion.
We are thrilled to announce that our plenary event will feature a keynote presentation from Dr. Ruha Benjamin, professor of African American Studies at Princeton University and author of "Race After Technology: Abolitionist Tools for the New Jim Code", which examines the relationship between machine bias and systemic racism, analyzing specific cases of “discriminatory design” and offering tools for a socially-conscious approach to tech development.
Immediately following Dr. Benjamin's keyote will be reactions and conversations with Dr. Alex Hanna (Google), and Dr. Anna Lauren Hoffmann (University of Washington), and a Q&A session with the audience.
The Plenary Event is scheduled for Friday, October 9, 2020 at 2:30pm CT.
Ruha Benjamin is a professor of African American Studies at Princeton University and author of People’s Science: Bodies and Rights on the Stem Cell Frontier (Stanford University Press). She has studied the social dimensions of science, technology, and medicine for over fifteen years and speaks widely on issues of innovation, equity, health, and justice in the U.S. and globally. She is also a Faculty Associate in the Center for Information Technology Policy; Program on History of Science; Center for Health and Wellbeing; Program on Gender and Sexuality Studies; Department of Sociology; and serves on the Executive Committees for the Program in Global Health and Health Policy and Center for Digital Humanities. Ruha is the recipient of many awards and honors, including the 2017 President's Award for Distinguished Teaching at Princeton. Her second book, Race After Technology: Abolitionist Tools for the New Jim Code, examines the relationship between machine bias and systemic racism, analyzing specific cases of “discriminatory design” and offering tools for a socially-conscious approach to tech development. She is also the editor of Captivating Technology.
Alex Hanna is a sociologist and research scientist working on machine learning fairness and ethical AI at Google. Before that, she was an Assistant Professor at the Institute of Communication, Culture, Information and Technology at the University of Toronto. Her research centers on origins of the training data which form the informational infrastructure of AI and algorithmic fairness frameworks, and the way these datasets exacerbate racial, gender, and class inequality.
Annal Lauren Hoffmann is a scholar and writer working at the intersections of data, technology, culture, and ethics. She currently is an Assistant Professor with The Information School at the University of Washington. Her work centers on issues in information, data, and ethics, paying specific attention to the ways discourse, design, and uses of information technology work to promote or hinder the pursuit of important human values like respect and justice.
This symposium is organized by the Department of Computer Science and the Center for Cyber Security Awareness and Cyber Defense at Marquette University, and the Northwestern Mutual Data Science Institute.
For additional information about this event, contact Dr. Michael Zimmer, Department of Computer Science, email@example.com, 414-228-5226.