STOLEN: The Algorithm That Rigged the Census: How One Bureaucrat Stole the House and Billions in Funding.

The 2020 census was marketed as an “actual enumeration,” a neutral count of people for apportionment and funding. It was not. The same official who helped block a basic citizenship question in 2018, John M. Abowd, then the Census Bureau’s Chief Scientist, pushed through a new, opaque methodology in 2020 called differential privacy. The new system deliberately injected mathematical noise into every block count in America, turning the census from a headcount into a model with knobs. The knob that mattered most was a single parameter, epsilon, a secrecy shroud known only to a small inner circle. Abowd argued that a single added question about citizenship posed an intolerable risk to data quality because there was, he said, not enough time to test it. Then he rushed an untested algorithm that altered every count in every neighborhood. The irony is so sharp it cuts: the man who warned that one question might distort the census approved a method that guaranteed distortion.

Start with the record. On January 19, 2018, Abowd sent Commerce a technical memo urging rejection of a citizenship question. He then testified for several days in federal court. The transcript, nearly 700 pages, cemented a narrative that any citizenship question would degrade data and impede participation. The courts cited this drumbeat of doubt, and the question was blocked. The administration lost the public fight. But the inside fight over how to publish the data was only beginning. Abowd immediately advanced a quiet revolution in disclosure avoidance, adopting differential privacy for the first time ever in a US census. That choice, made outside the glare that attended the citizenship question, had far more sweeping consequences.

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Plus: “If all this is true, President Trump’s call for a mid-decade census is more than justified.”