Protecting Your Privacy in a Data-Driven World

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A01=Claire McKay Bowen
anonymization methods
Author_Claire McKay Bowen
balancing data utility and privacy
Category=KCH
Category=PBT
Confidential Data
Data Access Layer
Data Adversary
Data confidentiality
Data Intruders
Data Privacy
Data privacy law
Data Privacy Laws
Data Privacy Protection
Data Stewards
Data Swapping
Differential Privacy
Disclosure Risk
Educational Materials
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
ethical data sharing
FEMA
GDPR
Longitudinal Business Database
North American Industry Classification System
Personal Data
privacy impact assessment
privacy preserving techniques
Privacy Researcher
quantitative research ethics
Santa Fe County
sensitive data analysis
Smart Phones
Social Network Data
Statistical disclosure control or limitation
Synthetic Data
Synthetic Data Generation
Utility Metrics
Validation Server

Product details

  • ISBN 9780367640774
  • Weight: 453g
  • Dimensions: 138 x 216mm
  • Publication Date: 22 Nov 2021
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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At what point does the sacrifice to our personal information outweigh the public good?

If public policymakers had access to our personal and confidential data, they could make more evidence-based, data-informed decisions that could accelerate economic recovery and improve COVID-19 vaccine distribution. However, access to personal data comes at a steep privacy cost for contributors, especially underrepresented groups.

Protecting Your Privacy in a Data-Driven World is a practical, nontechnical guide that explains the importance of balancing these competing needs and calls for careful consideration of how data are collected and disseminated by our government and the private sector. Not addressing these concerns can harm the same communities policymakers are trying to protect through data privacy and confidentiality legislation.

Dr. Claire McKay Bowen is the Lead Data Scientist for Privacy and Data Security at the Urban Institute. Her research focuses on developing and assessing the quality of di erentially private data synthesis methods and science communication. She holds a BS in mathematics and physics from Idaho State University and an MS and PhD in statistics from the University of Notre Dame. After completing her PhD, she worked at Los Alamos National Laboratory, where she investigated cosmic ray effects on supercomputers.

In 2021, the Committee of Presidents of Statistical Societies identified her as an emerging leader in statistics for her “contributions to the development and broad dissemination of Statistics and Data Science methods and concepts, particularly in the emerging field of Data Privacy, and for leadership of technical initiatives, professional development activities, and educational programs.”

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