In July 2018, the U.S. Census Bureau issued a Federal Register notice asking census data users to provide information about what data they used, at what level of geography, and how these use cases might affect different populations. This request for feedback did not announce to those users\u2014local governments, social scientists, and the public at large\u2014that its purpose was to facilitate a massive change in how data about the nation would be produced. A month later, the bureau\u2019s chief scientist, John Abowd, announced on a government blog the need to \u201cmodernize\u201d the system used for disclosure avoidance by turning to \u201cformal privacy\u201d methods. Such an approach would allow the government to renew its guarantee of the confidentiality of data. The description of this innovation did not convey the trade-off that would be discussed later, a trade-off that underpinned the Federal Register notice, a trade-off that pitted accuracy against confidentiality, and then pitted both against the desire for conventional statistical tables with numbers that appeared to resemble counts. Unaware of the broader context, the solicitation for feedback confounded data users and community advocates. Which data mattered? All of it, they answered. They needed all of the data, and it had to be accurate. As the reason for this question became clearer, data users grew upset, sides formed, coalitions coalesced, a controversy bloomed.<\/p>\n","protected":false},"excerpt":{"rendered":"
In July 2018, the U.S. Census Bureau issued a Federal Register notice asking census data users to provide information about what data they used, at what level of geography, and how these use cases might affect different populations. This request for feedback did not announce to those users\u2014local governments, social scientists, and the public at 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