The Center for Digital Humanities (CDH) is pleased to welcome Professor Lauren Klein from Georgia Tech who will be speaking on “ Who Counts? A Symposium on Intersectional Data,” on Monday, Oct. 22, at the CDH in Firestone Library, B Floor.
NYU Professor Mimi Onuoha, a 2011 Princeton alumna, will also be leading this forum on data feminism that will uncover and analyze the ways in which data practices—particularly those that abstract and classify individuals—replicate existing inequalities and institutionalize bias.
Profs. Klein and Onuoha will discuss how, far from being neutral,the ways in which data are gathered, curated, analyzed, described, stored, and communicated all serve as opportunities for bias. Using data visualization as a starting point, Professor Klein’s talk works backwards through the data-processing pipeline in order to show how a feminist approach not only exposes how power and privilege presently operate in visualization work, but also suggests how different design principles can help to mitigate inequality. Professor Onuoha, a Brooklyn-based artist and researcher, will respond with her thoughts about the implications of data collection and computational categorization.
This symposium, co-sponsored by the Program in Gender and Sexuality Studies, the Program in American Studies, and the Humanities Council, will focus on gaps, blanks, and absences and asks what might be done to foster practices at every stage in the data lifecycle that engage and represent the full spectrum of society.
Lauren Klein is an associate professor in the School of Literature, Media, and Communication at Georgia Tech, where she also directs the Digital Humanities Lab. She received her A.B. from Harvard University and her Ph.D. from the Graduate Center of the City University of New York (CUNY). Her research interests include the digital humanities, data visualization, and media studies.
Mimi Onuoha earned her MPS from NYU Tisch’s Interactive Telecommunications Program. She is currently Creative-in-Residence at Olin College for Engineering and an Adjunct Professor at NYU, where her work focuses on the overlap of digital and geographic spaces. She uses code, writing, interventions, and objects to explore missing data, automation, and the ways in which people are abstracted, represented, and classified. Currently she is combining ethnographic research methods with emerging data practices to investigate missing datasets as opportunities for grassroots data collection.