Wendy ChunNobel Conference 57

What if polarization is actually a goal of machine learning and big data--not an error accidentally produced by the methods and tools used in predictive data analytics? Wendy Chun believes that it is; she argues that these methods actually encode segregation, eugenics, and identity politics through the assumptions built into them at the ground level. To take just one instance, correlation is what enables big data to be used to make predictions about the future. But correlation stems from twentieth-century eugenic attempts to “breed” a better future. Predictive analytics is effectively designed to prevent the future from repairing the problems of the past.To desegregate networks, open the “echo chambers” and buttress social justice, Chun argues, we must develop alternative algorithms and interdisciplinary coalitions.

Chun is the author of several books, including the just-published Discriminating Data: Correlation, Neighborhoods and the New Politics of Recognition from which her lecture will be derived. The book investigates the centrality of race, gender, class and sexuality to machine learning and network analytics. 

Wendy Chun is founder of the Digital Democracy Institution, which she also leads. The Institute integrates research in the humanities and data sciences to address questions of equality and social justice. It seeks to combat the current proliferation of online “echo chambers” and discriminatory algorithms by creating alternative data literacies and paradigms for connection.

Wendy Chun is the Canada 150 Research Chair in New Media, School of Communication, Simon Fraser University. The recipient of Guggenheim, ACLS and American Academy of Berlin fellowships, she is a multidisciplinary researcher, with an undergraduate degree in systems design engineering from the University of Waterloo, and a PhD in English literature from Princeton.