Privacy, big data, and the public good : frameworks for engagement / edited by Julia Lane, American Institutes for Research, Washington DC, Victoria Stodden, Columbia University, Stefan Bender, Institute for Employment Research of the German Federal Employment Agency, Helen Nissenbaum, New York University.

Contributor(s): Material type: TextTextPublisher: New York, NY : Cambridge University Press, 2014Description: xix, 322 pages ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781107067356
  • 1107067359
  • 9781107637689
  • 1107637686
Subject(s): DDC classification:
  • 323.44/8 23
LOC classification:
  • JC596 .P747 2014
Contents:
Part I. Conceptual framework. Monitoring, datafication, and consent : legal approaches to privacy in the big data context / Katherine J. Strandburg ; Big data's end run around anonymity and consent / Solon Barocas and Helen Nissenbaum ; The economics and behavioral economics of privacy / Alessandro Acquisti ; Changing the rules : general principles for data use and analysis / Paul Ohm ; Enabling reproducibility in big data research : balancing confidentiality and scientific transparency / Victoria Stodden -- Part II. Practical framework. The value of big data for urban science / Steven E. Koonin and Michael J. Holland ; Data for the public good : challenges and barriers in the context of cities / Robert M. Goerge ; A European perspective on research and big data analysis / Peter Elias ; The new deal on data : a framework for institutional controls / Daniel Greenwood, Arkadiusz Stopczynski, Brian Sweatt, Thomas Hardjono, and Alex Pentland ; Engineered controls for dealing with big data / Carl Landwehr ; Portable approaches to informed consent and open data / John Wilbanks -- Part III. Statistical framework. Extracting information from big data : issues of measurement, inference and linkage / Frauke Kreuter and Roger D. Peng ; Using statistics to protect privacy / Alan F. Karr and Jerome P. Reiter ; Differential privacy: a cryptographic approach to private data analysis / Cynthia Dwork.
Summary: 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.--Publisher information.
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Books Books Odessa College Stacks 323.448 P961LP (Browse shelf(Opens below)) 1 Available 51994001711722

Includes bibliographical references and index.

Part I. Conceptual framework. Monitoring, datafication, and consent : legal approaches to privacy in the big data context / Katherine J. Strandburg ; Big data's end run around anonymity and consent / Solon Barocas and Helen Nissenbaum ; The economics and behavioral economics of privacy / Alessandro Acquisti ; Changing the rules : general principles for data use and analysis / Paul Ohm ; Enabling reproducibility in big data research : balancing confidentiality and scientific transparency / Victoria Stodden -- Part II. Practical framework. The value of big data for urban science / Steven E. Koonin and Michael J. Holland ; Data for the public good : challenges and barriers in the context of cities / Robert M. Goerge ; A European perspective on research and big data analysis / Peter Elias ; The new deal on data : a framework for institutional controls / Daniel Greenwood, Arkadiusz Stopczynski, Brian Sweatt, Thomas Hardjono, and Alex Pentland ; Engineered controls for dealing with big data / Carl Landwehr ; Portable approaches to informed consent and open data / John Wilbanks -- Part III. Statistical framework. Extracting information from big data : issues of measurement, inference and linkage / Frauke Kreuter and Roger D. Peng ; Using statistics to protect privacy / Alan F. Karr and Jerome P. Reiter ; Differential privacy: a cryptographic approach to private data analysis / Cynthia Dwork.

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.--Publisher information.

Text in English.

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