danah boyd Publishes Balancing Data Utility and Confidentiality in the 2020 US Census
A new living document by Data & Society Founder and President and alum danah boyd, Balancing Data Utility and Confidentiality in the 2020 US Census, explains how differential privacy works in the context of the US Census and illuminates key conversations, misunderstandings, and anxieties surrounding this disclosure avoidance system.
In the age of commercial data and advanced computer science, the US Census Bureau is implementing a new technical system to ensure the confidentiality of individual data in the 2020 census. This system is based on a mathematical technique known as “differential privacy.”
Differential privacy allows the Census Bureau to mathematically balance between privacy and data utility. By examining how much risk there is of reconstructing identifying information from a particular census statistical table, the Census Bureau can ensure a certain degree of confidentiality by inserting noise in strategic places. Previous disclosure avoidance systems could not withstand the risks brought on by the increase in commercial data from data-centric technologies.
With useful insights for academics, civil society, data users, and anyone concerned about their privacy in the 2020 census, boyd uses this living document to clarify the motivations, risks, and unknowns surrounding differential privacy. She calls for communication, collaboration, and understanding between all parties tackling the trade-offs between confidentiality and accuracy.
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