Ethical reasoning in big data : an exploratory analysis /
"This book springs from a multidisciplinary, multi-organizational, and multi-sector conversation about the privacy and ethical implications of research in human affairs using big data. The need to cultivate and enlist the public's trust in the abilities of particular scientists and scienti...
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Group Author: | ; |
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Published: |
Springer,
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Publisher Address: | Switzerland : |
Publication Dates: | [2016] |
Literature type: | Book |
Language: | English |
Series: |
Computational social sciences. |
Subjects: | |
Summary: |
"This book springs from a multidisciplinary, multi-organizational, and multi-sector conversation about the privacy and ethical implications of research in human affairs using big data. The need to cultivate and enlist the public's trust in the abilities of particular scientists and scientific institutions constitutes one of this book's major themes. The advent of the Internet, the mass digitization of research information, and social media brought about, among many other things, the ability to harvest {u2013} sometimes implicitly {u2013} a wealth of human genomic, biological, behavioral, economic, political, and social data for the purposes of scientific research as well as commerce, government affairs, and social interaction. What type of ethical dilemmas did such changes generate? How should scientists collect, manipulate, and disseminate this information? The effects of this revolution and its ethical implications are wide-ranging. This book includes the opinions of myriad investigators, practitioners, and stakeholders in big data on human beings who also routinely reflect on the privacy and ethical issues of this phenomenon. Dedicated to the practice of ethical reasoning and reflection in action, the book offers a range of observations, lessons learned, reasoning tools, and suggestions for institutional practice to promote responsible big data research on human affairs. It caters to a broad audience of educators, researchers, and practitioners. Educators can use the volume in courses related to big data handling and processing. Researchers can use it for designing new methods of collecting, processing, and disseminating big data, whether in raw form or as analysis results. Lastly, practitioners can use it to steer future tools or procedures for handling big data. As this topic represents an area of great interest that still remains largely undeveloped, this book is sure to attract significant interest by filling an obvious gap in currently available literature"--Provided by publisher. |
Carrier Form: | x, 192 pages : illustrations (some color) ; 25 cm. |
Bibliography: | Includes bibliographical references. |
ISBN: |
9783319284200 3319284207 |
Index Number: | QA76 |
CLC: | TP311.13-05 |
Call Number: | TP311.13-05/E842 |
Contents: | Part I. Applying a contextual analysis of privacy in big data research -- A theoretical framework for ethical reflection in big data research / Michael Steinmann, Sorin Adam Mataei and Jeff Collmann -- Part II. Ethical reasoning beyond privacy in big data -- The privacy preferences of Americans / Lee Rainie -- Engaging the public in ethical reasoning about big data / Justin Anthony Knapp -- The ethics of large-scale genomic research / Benjamin E. Berkman, Zachary E. Shapiro, Lisa Eckstein and Elizabeth R. Pike -- Neurotechnological convergence and "big data": a force-multiplier toward advancing neuroscience / Diane DiEuliis and James Giordano -- Data ethics: attaining personal privacy on the Web / Lisa Singh -- Part III. Institutionalizing ethical reasoning about big data -- Technology for privacy assurance / J.C. Smart -- Institutionalizing ethical reasoning: integrating the ASA's ethical guidelines for professional practice into course, program, and curriculum / Rochelle E. Tractenberg -- Data management plans, institutional review boards, and the ethical management of big data about human subjects / Jeff Collmann, Kevin T. FitzGerald, Samantha Wu, Josel Kupersmith and Sorin Adam Matei -- Integrating ethical reasoning into preparation for participation to work in/with big data through the stewardship model / Rochelle E. Tractenberg. |