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The application of machine learning technology for issues of poverty has become a widely discussed desire in international development circles. Joshua Blumenstock, assistant professor at the UC Berkeley School of Information and director of the Data-Intensive Development Lab, cautions that these new digital methods must be used as a complement to more traditional approaches, not as a replacement.

At a Blum Center for Developing Economies Faculty Salon, Blumenstock highlighted ways big data is altering the field of international development. Big data sets from recent years paired with machine learning technology have produced fascinating and controversial work that Blumenstock says, must be evaluated carefully to develop nuanced understandings of those affected by poverty and its potential solution methods.

UC Berkeley and 20 other universities are forming a new consortium, the Public Interest Technology University Network (PIT-UN), to support the development of new technologies, and to explore what policies and safeguards must be put into place to ensure that they will work for the benefit of society.

Berkeley News spoke with Deirdre Mulligan, associate professor in Berkeley’s School of Information and faculty director of the Berkeley Center for Law and Technology, about Berkeley’s long-standing commitment to supporting research and teaching that explores the social and political consequences of technology and develops strategies and methods to advance human rights and social welfare.