The Class Differential in Data Privacy | Michele Gilman
Data & Society Faculty Fellow Michele Gilman discusses the ways that data-centric technologies adversely impact low-income communities. In her talk, Gilman argues there is a class differential in privacy law that harms poor people, but that poverty lawyers and their clients are working to challenge this differential in order to advance economic justice.

Feminist Data Futures and Relational Infrastructures | Anita Say Chan
Data & Society Fellow Anita Say Chan shares her work on data justice networks and research collectives in the global Americas, exploring their shared genealogies with feminist data methods developed at the turn of the century.

The Depth of the Data | Dan Bouk
Data isn’t simple, thin, or objective. Data has depth, that can and must be read deeply. Data & Society Fellow Dan Bouk demonstrates such reading in this talk with democracy’s data, the data produced by the U.S. census.

Data & Society’s Director of Research Sareeta Amrute moderates the discussion and audience Q&A. Learn more about our fellows work, wide-ranging interdisciplinary connections, and a few of the provocative questions that have emerged this year.