A group of Harvard researchers has come out against the U.S. Census Bureau’s use of a controversial method to protect privacy with the numbers used for redrawing congressional and legislative districts, saying it doesn’t produce data good enough for redistricting.
The Harvard researchers said in a paper released last week that using the new privacy method will make it impossible for states to comply with the requirement that districts have equal populations, a principle also known as “One Person, One Vote.” The technique also doesn’t universally protect the privacy of people who participated in the 2020 census, they said.
The privacy method adds “noise,” or intentional errors, to the data to obscure the identity of any given participant in the 2020 census while still providing statistically valid information. Rather than use this technique, known as “differential privacy,” the researchers said the Census Bureau should rely on a privacy method used in the 2010 census, when data in some households were swapped with other households.
“Over the past half century, the Supreme Court has firmly established the principle of One Person, One Vote, requiring states to minimize the population difference across districts based on the Census data,” they wrote. Differential privacy makes it “impossible to follow this basic principle.”
The technique “negatively impacts the redistricting process and voting rights of minority groups without providing clear benefits,” the researchers said.