Date/Time
Date(s) - 20/03/2024
4:00 pm - 5:30 pm
Categories
Invited talk by Milagros Miceli (Weizenbaum-Institut) and Julian Posada (Yale University) – Online
Milagros Miceli is a sociologist and computer scientist leading the Data, Algorithmic Systems, and Ethics research group at the Weizenbaum-Institut for the Networked Society in Berlin. Her research explores the production of ground-truth data for machine learning, with a specific focus on data labor, and the power relations that condition dataset production processes. In addition, Miceli is a researcher at Distributed AI Research Institute where she explores ways of engaging with communities of data workers in AI research and development.
Julian Posada is an Assistant Professor of American Studies at Yale University and a member of the Yale Law School’s Information Society Project and the Yale Institute for Foundations of Data Science. His research investigates the human labor for data production in the artificial intelligence industry, emphasizing the experiences of workers in Latin America who are employed by digital platforms to produce data for machine learning and validate algorithmic outputs.
In this seminar conversation, Miceli and Posada will join forces to discuss how current power imbalances and experiences in data work contribute to the (re)production of social inequalities by machine learning, and the importance of enhancing labor conditions for data workers in the process of improving data quality for machine learning to mitigate these issues.
The seminar will be introduced by Thomas Poell, who is a Professor of Data, Culture & Institutions at the University of Amsterdam, program director MA Media Studies, and director of the Research Priority Area on Global Digital Cultures.