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Can a Set of Equations Keep U.S. Census Data Private?


The agency generated some 7.8 billion statistics about the 308 million people counted in the 2010 census.

The U.S. Census Bureau will apply a mathematical concept called differential privacy to its release of 2020 census data, after conducting experiments that suggest current approaches cannot assure confidentiality.

Credit: William Duke

The U.S. Census Bureau is making waves among social scientists with what it calls a "sea change" in how it plans to safeguard the confidentiality of data it releases from the decennial census.

The agency announced in September 2018 that it will apply a mathematical concept called differential privacy to its release of 2020 census data after conducting experiments that suggest current approaches can't assure confidentiality. But critics of the new policy believe the Census Bureau is moving too quickly to fix a system that isn't broken. They also fear the changes will degrade the quality of the information used by thousands of researchers, businesses, and government agencies.

The move has implications that extend far beyond the research community. Proponents of differential privacy say a fierce, ongoing legal battle over plans to add a citizenship question to the 2020 census has only underscored the need to assure people that the government will protect their privacy.

 

From Science
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