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Operationalizing Expectations and Mapping Challenges of Information Privacy and Data Protection Measures: A Machine-Generated Literature Overview

Operationalizing Expectations and Mapping Challenges of Information Privacy and Data Protection Measures: A Machine-Generated Literature Overview

          
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About the Book

This book offers a machine-generated literature overview of the legal and ethical considerations, in the context of technological growth, over implementing privacy and data protection measures in the last three decades. It showcases the expectations and challenges in mapping and operationalizing the information privacy and data protection measures. It is the second of a two volume exploration of the narrative, wherein both volumes have consciously tried to remain both jurisdictional and technology neutral while considering a range of data protection and privacy issues. Towards that end, this volume addresses these issues at a conceptual level while dealing with the question of implementing data protection expectations in different environments. It, however, looks at the operational question of implementing the expectations, positioning itself in a context of 'conflict' and 'uneasiness' that often is assigned to the question of technology and privacy. Therefore, it starts with a chapter on these conflicts and contradictions before moving on to articles that effectively implement data protection principles in a tech environment. The second chapter gives us a sense of how privacy and data protection issues are no longer obscure incidents that happen to strangers. The following chapter provides a snapshot of examples where technical advancements offer effective and practical solutions in implementing data protection measures to protect the privacy of individuals. The final two chapters portray the extent of risks that individuals face in the tech environment and how often privacy and data protection questions come between technical growth and advancement.

The first volume, titled 'Expectations vs Realities of Information Privacy and Data Protection Measures', captures overarching issues about data protection and privacy; conceptualizes data protection from different perspectives and its existing debates with other rights and developments in a democratic society; provides a snapshot of developments happening in various jurisdictions and how data protection framework engages with other laws. It also broaches the critical issue of consent and how consent as a requirement has evolved and integrated with health research and other allied areas. The effective interventions by the human expert in both volumes add immense value to the machine-generated content and highlight future trends of research. The volumes are an invaluable resource for not only researchers, but also policy makers, practitioners, corporate sector, across disciplines, and anyone looking to get an idea about the evolution of privacy, data protection issues and how these issues stand with technological growth in the last three decades since 1990.


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Product Details
  • ISBN-13: 9789819973705
  • Publisher: Springer Nature Singapore
  • Publisher Imprint: Springer
  • Language: English
  • Sub Title: A Machine-Generated Literature Overview
  • ISBN-10: 9819973708
  • Publisher Date: 29 Dec 2023
  • Binding: Hardback
  • Returnable: Y


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Operationalizing Expectations and Mapping Challenges of Information Privacy and Data Protection Measures: A Machine-Generated Literature Overview
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