Join us for the Love Data Week virtual keynote presentation by Lauren Klein, author of Data Feminism (MIT Press, 2020).
In “Data Feminism”, Klein and her coauthor Catherine D’Ignazio established a set of principles for doing more just and equitable data science. Informed by the past several decades of intersectional feminist activism and critical thought, the principles of data feminism modeled how to examine and challenge power, rethink binaries and hierarchies, elevate emotion and embodiment, consider context, embrace pluralism, and make labor visible. How can these principles be applied to the current conversation about AI, its present harms, and its future possibilities? This talk will briefly summarize the principles of data feminism before moving to a set of examples that show how these principles can be applied–and extended–to our current technological landscape.
Free and open to all. Registration required for Zoom link.
Presented by Becker Medical Library, Washington University Libraries and the Institute for Informatics, Data Science & Biostatistics (I2DB)
Lauren Klein is Winship Distinguished Research Professor and Associate Professor in the departments of Quantitative Theory & Methods and English at Emory University, where she also directs the Digital Humanities Lab. Lauren works at the intersection of data science, AI, and the humanities, with an emphasis on questions of gender and race. She is co-author (with Catherine D’Ignazio) of the award-winning Data Feminism (MIT Press, 2020) and co-editor (with Matthew K. Gold) of Debates in the Digital Humanities (Univ. of Minnesota Press), among other publications. She is currently completing Data by Design: An Interactive History of Data Visualization, forthcoming from the MIT Press, and envisioning the Atlanta Interdisciplinary AI Network, which will launch in Fall 2023.
About Love Data Week
During Love Data Week we celebrate all things data, sharing resources and making connections to help ensure that all students and scholars at WashU are able to access, analyze, and utilize data.