Kenny, Christopher T., Shiro Kuriwaki, Cory McCartan, Evan Rosenman, Tyler Simko, and Kosuke Imai. (2023). ``Comment: The Essential Role of Policy Evaluation for the 2020 Census Disclosure Avoidance System.'' Harvard Data Science Review, Special Issue 2: Dierential Privacy for the 2020 U.S. Census (January), pp. 1-16.

In "Differential Perspectives: Epistemic Disconnects Surrounding the US Census Bureau's Use of Differential Privacy," boyd and Sarathy argue that empirical evaluations of the Census Disclosure Avoidance System (DAS), including our published analysis, failed to recognize how the benchmark data against which the 2020 DAS was evaluated is never a ground truth of population counts. In this commentary, we explain why policy evaluation, which was the main goal of our analysis, is still meaningful without access to a perfect ground truth. We also point out that our evaluation leveraged features specific to the decennial Census and redistricting data, such as block-level population invariance under swapping and voter file racial identification, better approximating a comparison with the ground truth. Lastly, we show that accurate statistical predictions of individual race based on the Bayesian Improved Surname Geocoding, while not a violation of differential privacy, substantially increases the disclosure risk of private information the Census Bureau sought to protect. We conclude by arguing that policy makers must confront a key trade-off between data utility and privacy protection, and an epistemic disconnect alone is insufficient to explain disagreements between policy choices.

Kenny, Christopher, Cory McCartan, Shiro Kuriwaki, Tyler Simko, and Kosuke Imai. (2024). ``Evaluating Bias and Noise Induced by the U.S. Census Bureau's Privacy Protection Methods.'' Science Advances, Vol 10, No. 18 (May), pp. 1-13.

McCartan, Cory, Tyler Simko, and Kosuke Imai. (2023). ``Making Differential Privacy Work for Census Data Users.'' Harvard Data Science Review, Vol. 5, No. 4 (Fall).

Kenny, Christopher, Cory McCartan, Tyler Simko, and Kosuke Imai. (2024). ``Census officials must constructively engage with independent evaluations.'' Proceedings of the National Academy of Sciences (Letter), Vol. 121, No. 11, e2321196121.

Kenny, Christopher T., Shiro Kuriwaki, Cory McCartan, Evan Rosenman, Tyler Simko, and Kosuke Imai. ``The Use of Differential Privacy for Census Data and its Impact on Redistricting: The Case of the 2020 U.S. Census..'' Science Advances, Vol. 7, No. 7 (October), pp. 1-17.