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Massive amounts of data on human beings can now be analyzed. Pragmatic purposes abound, including selling goods and services, winning political campaigns, and identifying possible terrorists. Yet 'big data' can also be harnessed to serve the public good: scientists can use big data to do research that improves the lives of human beings, improves government services, and reduces taxpayer costs. In order to achieve this goal, researchers must have access to this data - raising important privacy questions. What are the ethical and legal requirements? What are the rules of engagement? What are the best ways to provide access while also protecting confidentiality? Are there reasonable mechanisms to compensate citizens for privacy loss? The goal of this book is to answer some of these questions. The book's authors paint an intellectual landscape that includes legal, economic, and statistical frameworks. The authors also identify new practical approaches that simultaneously maximize the utility of data access while minimizing information risk.
Info autore
Julia Lane is Senior Managing Economist for the American Institutes for Research in Washington, DC. She holds honorary positions as Professor of Economics at the BETA University of Strasbourg CNRS, chercheur associée at Observatoire des Sciences et des Techniques, Paris, and professor at the University of Melbourne's Institute of Applied Economics and Social Research.Victoria Stodden is Assistant Professor of Statistics at Columbia University and is affiliated with the Columbia University Institute for Data Sciences and Engineering.Stefan Bender is head of the Research Data Center (RDC) at the German Federal Employment Agency in the Institute for Employment Research (IAB).Helen Nissenbaum is Professor of Media, Culture, and Communication and Computer Science at New York University, where she is also director of the Information Law Institute.
Riassunto
The book discusses access to big data for city, state, and federal government agencies and legal, social science, statistical, and technical communities interested in enabling research on big data. The authors' goal is to move the conversation to a vision of what frameworks should and could guide data access.
