Protecting Your Privacy in a Data-Driven World

List of contents

1. Why Is Data Privacy Important? 2. How Did Data Privacy Change Over Time? 3. How Do Data Privacy Methods Expand Access to Data? 4. How Do Data Privacy Methods Avoid Invalidating Results? 5. What Makes Datasets Difficult for Data Privacy? 6. What Data Privacy Laws Exist? 7. What Is the Future of Data Privacy?

About the author

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.”

Summary

Does sacrifice to personal information outweigh public good? Access to personal and confidential data allows for more evidence-based, data-informed decisions that can accelerate economic recovery, improve COVID-19 vaccine distribution. However, access comes at a steep privacy cost for contributors, especially underrepresented groups.

Product details

• Authors: Claire McKay Bowen
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 30.11.2021
• EAN: 9780367640743
• ISBN: 978-0-367-64074-3
• No. of pages: 134
• Series: ASA-CRC Series on Statistical Reasoning in Science and Society
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Social sciences, law, business > Business > General, dictionaries; MATHEMATICS / Probability & Statistics / General, Economic statistics, Probability & statistics, Probability and statistics, Econometrics and economic statistics