Challenges and New Approaches for Protecting Privacy in Federal Statistical Programs: A Workshop

Workshop

June 6 - 7, 2019

Past

Agenda

Download the Agenda

Materials

Workshop Flyer

About

For decades, federal statistical agencies have striven to balance the legal and ethical obligations to protect the confidentiality of data subjects with the need to provide informative statistics and access to data for secondary analysis. In recent years, balancing these objectives has become increasingly difficult. The digital revolution has seen an explosion in the growth of available data, both from public and private sources, which ill-intentioned actors could use to compromise confidentiality protections.
This workshop will discuss new approaches to protecting data confidentiality, with a particular focus on methods that offer formal guarantees of privacy protection, like differential privacy. Discussions will cover the policy and implementation issues from both provider and user perspectives, including the promises and limitations of using formal privacy methods.

Videos from the workshop can be found here.

Contact

Jillian Kaufman

(202) 334-3465
jkaufman@nas.edu

Location

National Academy of Sciences Building

2101 Constitution Ave NW

Washington DC 20418, USA

Disclaimer

It is essential to the National Academies mission of providing evidence-based advice that participants in any of our meetings or events avoid political or partisan statements or commentary and maintain a culture of mutual respect. The statements and presentations during our meetings or events are solely those of the individual participants and do not necessarily represent the views of other participants or the National Academy of Sciences, which is a non-partisan, tax exempt organization that includes under its Charter the National Academy of Engineering and National Academy of Medicine, and that operates the National Research Council.

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Challenges and New Approaches for Protecting Privacy in Federal Statistical Programs: A Workshop

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Challenges and New Approaches for Protecting Privacy in Federal Statistical Programs: A Workshop