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Privacy, Poverty, And Big Data: A Matrix Of Vulnerabilities For Poor Americans, Mary Madden, Michele E. Gilman, Karen Levy, Alice Marwick

All Faculty Scholarship

This Article examines the matrix of vulnerabilities that low-income people face as a result of the collection and aggregation of big data and the application of predictive analytics. On one hand, big data systems could reverse growing economic inequality by expanding access to opportunities for low-income people. On the other hand, big data could widen economic gaps by making it possible to prey on low-income people or to exclude them from opportunities due to biases entrenched in algorithmic decision-making tools. New kinds of “networked privacy” harms, in which users are simultaneously held liable for their own behavior and the actions …