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Overview

Perspectives on the varied challenges posed by big data for health, science, law, commerce, and politics.

Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identify linguistic correlations in large corpuses of texts. This book examines big data not as an undifferentiated whole but contextually, investigating the varied challenges posed by big data for health, science, law, commerce, and politics. Taken together, the chapters reveal a complex set of problems, practices, and policies.

The advent of big data methodologies has challenged the theory-driven approach to scientific knowledge in favor of a data-driven one. Social media platforms and self-tracking tools change the way we see ourselves and others. The collection of data by corporations and government threatens privacy while promoting transparency. Meanwhile, politicians, policy makers, and ethicists are ill-prepared to deal with big data's ramifications. The contributors look at big data's effect on individuals as it exerts social control through monitoring, mining, and manipulation; big data and society, examining both its empowering and its constraining effects; big data and science, considering issues of data governance, provenance, reuse, and trust; and big data and organizations, discussing data responsibility, “data harm,” and decision making.

Contributors
Ryan Abbott, Cristina Alaimo, Kent R. Anderson, Mark Andrejevic, Diane E. Bailey, Mike Bailey, Mark Burdon, Fred H. Cate, Jorge L. Contreras, Simon DeDeo, Hamid R. Ekbia, Allison Goodwell, Jannis Kallinikos, Inna Kouper, M. Lynne Markus, Michael Mattioli, Paul Ohm, Scott Peppet, Beth Plale, Jason Portenoy, Julie Rennecker, Katie Shilton, Dan Sholler, Cassidy R. Sugimoto, Isuru Suriarachchi, Jevin D. West

Product Details

ISBN-13: 9780262529488
Publisher: MIT Press
Publication date: 10/21/2016
Series: Information Policy
Pages: 312
Product dimensions: 6.90(w) x 8.90(h) x 0.70(d)
Age Range: 18 Years

About the Author

Cassidy R. Sugimoto is Associate Professor in the School of Informatics and Computing at Indiana University Bloomington and the coeditor of Beyond Bibliometrics (MIT Press).

Hamid R. Ekbia is Professor of Informatics, Cognitive Science, and International Studies, andDirector of the Center for Research on Mediated Interaction at Indiana University Bloomington. He is the author of Artificial Dreams: The Quest for Non-Biological Intelligence and a coeditor of Big Data Is Not a Monolith (MIT Press).

Michael Mattioli is Associate Professor at the Indiana University Maurer School of Law.

Diane E. Bailey is Associate Professor in the School of Information at the University of Texas at Austin.

Table of Contents

Series Editor's introduction vii

Acknowledgments ix

Introduction Hamid R. Ekbia Cassidy R. Sugimoto Michael Mattioli xi

I Big Data and Individuals 1

1 Big Data, Consent, and the Future of Data Protection Fred H. Cate 3

2 When They Are Your Big Data: Participatory Data Practices as a Lens on Big Data Katie Shilton 21

3 Wrong Side of the Tracks Simon DeDeo 31

II Big Data and Society 43

4 What If Everything Reveals Everything? Paul Ohm Scott Peppet 45

5 Big Data in the Sensor Society Mark Burdon Mark Andrejevic 61

6 Encoding the Everyday: The Infrastructural Apparatus of Social Data Cristina Alaimo Jannis Kallinikos 77

III Big Data and Science 91

7 Big Genomic Data and the State Jorge L. Contreras 93

8 Trust Threads: Minimal Provenance for Data Publishing and Reuse Beth Plale Inna Kouper Allison Goodwell Isuru Suriarachchi 105

9 Can We Anticipate Some Unintended Consequences of Big Data? Kent R. Anderson 117

10 The Data Gold Rush in Higher Education Jevin D. West Jason Portenoy 129

IV Big Data and Organizations 141

11 Obstacles on the Road to Corporate Data Responsibility M. Lynne Markus 143

12 Will Big Data Diminish the Role of Humans in Decision Making? Michael Bailey 163

13 Big Data in Medicine: Potential, Reality, and Implications Dan Sholler Diane E. Bailey Julie Rennecker 173

14 Hal the Inventor: Big Data and Its Use by Artificial Intelligence Ryan Abbott 187

Conclusion Cassidy R. Sugimoto Michael Mattioli Hamid R. Ekbia 199

Notes 213

References 225

Contributors 267

Index 275

What People are Saying About This

Alan Porter

Big data pervades and crosses organizations and domains, posing multiple challenges, yet these challenges are dwarfed by the opportunities and issues posed by big data analytics (BDA).For a researcher working on BDA, this volume opens multiple perspectives on an amazingly rich cross-section of those and explores what to do about them.

Eric T. Meyer

Big Data Is Not a Monolith is required reading for those who find themselves in the thrall of big data but want to move beyond the hype to understand the social context of the current big data computerization movement. The collected authors ably grapple with how big data as a socio-technical system contributes to knowledge, shapes human behavior and choices, and has become increasingly integral to our social, legal, political, and economic systems.

From the Publisher

Big data pervades and crosses organizations and domains, posing multiple challenges, yet these challenges are dwarfed by the opportunities and issues posed by big data analytics (BDA). For a researcher working on BDA, this volume opens multiple perspectives on an amazingly rich cross-section of those and explores what to do about them.

Alan Porter , codirector of the Program in Science, Technology & Innovation Policy (STIP), Georgia Tech

This book combines expertise from different areas of scholarship to give valuable insights into what big data is doing, what it can do, and what it should be allowed to do. It is essential reading for those wishing to understand the widespread societal implications of the big data revolution.

Mike Thelwall , Professor of Information Science, University of Wolverhampton

Big Data Is Not a Monolith is required reading for those who find themselves in the thrall of big data but want to move beyond the hype to understand the social context of the current big data computerization movement. The collected authors ably grapple with how big data as a socio-technical system contributes to knowledge, shapes human behavior and choices, and has become increasingly integral to our social, legal, political, and economic systems.

Eric T. Meyer , Professor of Social Informatics, University of Oxford; coauthor of Knowledge Machines: Digital Transformations of the Sciences and Humanities

Endorsement

Big Data Is Not a Monolith is required reading for those who find themselves in the thrall of big data but want to move beyond the hype to understand the social context of the current big data computerization movement. The collected authors ably grapple with how big data as a socio-technical system contributes to knowledge, shapes human behavior and choices, and has become increasingly integral to our social, legal, political, and economic systems.

Eric T. Meyer, Professor of Social Informatics, University of Oxford; coauthor of Knowledge Machines: Digital Transformations of the Sciences and Humanities

Mike Thelwall

This book combines expertise from different areas of scholarship to give valuable insights into what big data is doing, what it can do, and what it should be allowed to do. It is essential reading for those wishing to understand the widespread societal implications of the big data revolution.

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