Privacy, Big Data, and the Public Good: Frameworks for Engagement

. Ed(s): Lane, Julia; Stodden, Victoria; Bender, Stefan; Nissenbaum, Helen

ISBN 10: 1107067359 / ISBN 13: 9781107067356

Published by Cambridge University Press, 2014

About this Item

Data access is essential for serving the public good. This book provides new frameworks to address the resultant privacy issues. Editor(s): Lane, Julia; Stodden, Victoria; Bender, Stefan; Nissenbaum, Helen. Num Pages: 344 pages, 4 b/w illus. BIC Classification: JHB; UBJ. Category: (U) Tertiary Education (US: College). Dimension: 162 x 235 x 23. Weight in Grams: 598. . 2014. 1st Edition. hardcover. . . . . Books ship from the US and Ireland.

Seller Inventory # V9781107067356

Bibliographic Details

• Title: Privacy, Big Data, and the Public Good: Frameworks for Engagement
• Publisher: Cambridge University Press
• Publication Date: 2014
• Language: English
• ISBN 10: 1107067359
• ISBN 13: 9781107067356
• Binding: Hardcover
• Condition: New

About this title

Synopsis

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.

About the Authors

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.