Co-Opting AI: Origins | Virtual Event
NYU’s Institute for Public Knowledge, Sloane Lab, and the Karsh Institute of Democracy at the University of Virginia invite you to a new discussion in the series “Co-Opting AI.” This will be a completely virtual event. A Zoom link will be sent to all registrants the day prior to the event.
This event will “take a step back” and trace the origins of AI and the various inventions and technologies that comprise it.
Stephanie Dick is an Assistant Professor in the School of Communication at Simon Fraser University and holds a PhD in History of Science from Harvard University. Her research and teaching focus on the history of computing, mathematics, and artificial intelligence since the Second World War. She is co-editor, with Janet Abbate, of Abstractions and Embodiments: New Histories of Computing and Society (Johns Hopkins University Press, 2022). Her first book project, Making Up Minds: Computing and Proof in the Postwar United States, explores attempts to reproduce human intelligence, mathematical intelligence in particular, in computers and the theories of human cognitive faculties that informed these efforts. Her second project explores the development of early computerized law enforcement databanks in the 1960s and 70s United States, along with the automated identification tools that were developed in tandem. She co-edits the “Mining the Past” column at the Harvard Data Science Review, serves on the editorial board of the IEEE Annals of the History of Computing, and is a co-organizer of the annual SIGCIS conference.
Kevin Driscoll is the author of The Modem World: A Prehistory of Social Media, co-author of Minitel: Welcome to the Internet, and maintainer of the Minitel Research Lab, USA with Julien Mailland. He is an associate professor of media studies at the University of Virginia. This is his homepage.
Chris Wiggins is an associate professor of applied mathematics at Columbia University and the Chief Data Scientist at The New York Times. At Columbia he is a founding member of the executive committee of the Data Science Institute, and of the Department of Applied Physics and Applied Mathematics as well as the Department of Systems Biology, and is affiliated faculty in Statistics. He is a co-founder and co-organizer of hackNY, a nonprofit which since 2010 has organized the hackNY Fellows Program, a structured summer internship at NYC startups. Prior to joining the faculty at Columbia he was a Courant Instructor at NYU (1998-2001) and earned his PhD at Princeton University (1993-1998) in theoretical physics. He is a Fellow of the American Physical Society and is a recipient of Columbia’s Avanessians Diversity Award. His book “Data Science in Context: Foundations, Challenges, Opportunities“, with Alfred Spector, Peter Norvig, and Jeannette M. Wing, was published by Cambridge University Press in October, 2022. His book “How Data Happened: A History from the Age of Reason to the Age of Algorithms“, with Matthew L. Jones, was published by Norton Press in March 2023.
Mona Sloane, Ph.D., is an Assistant Professor of Data Science and Media Studies at the University of Virginia (UVA). As a sociologist, she studies the intersection of technology and society, specifically in the context of AI design, use, and policy. She also convenes the Co-Opting AI series and serves as the Technology Editor for Public Books. At UVA, Mona runs Sloane Lab which conducts empirical research on the implications of technology for the organization of social life. Its focus lies on AI as a social phenomenon that intersects with wider cultural, economic, material, and political conditions. The lab spearheads social science leadership in applied work on responsible AI, public scholarship, and technology policy.
The Co-Opting AI event series is convened by Mona Sloane. It is hosted by NYU’s Institute for Public Knowledge, UVA’s Karsh Institute of Democracy, and Sloane Lab.