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Researchers find weaknesses in current strategies for protecting privacy inlarge datasets. Many anonymized datasets are reidentifiable, and norms foroffering data subjects notice and consent over emphasize individualresponsibility. Based on fieldwork with data managers in the City of Seattle, Iidentify ways that these conventional approaches break down in practice.Drawing on work from theorists in sociocultural anthropology, I propose that aHuman Centered Data Science move beyond concepts like dataset identifiabilityand sensitivity toward a broader ontology of who is implicated by a dataset,and new ways of anticipating how data can be combined and used.

A Human-Centered Approach to Data Privacy : Political Economy, Power, and Collective Data Subjects