Position: Challenges and Opportunities for Differential Privacy in the U.S. Federal Government

TL;DR

This paper discusses the challenges and potential opportunities for implementing differential privacy in the U.S. federal government, highlighting specific use cases and the need for policy and technical advancements.

Contribution

It identifies key challenges restricting differential privacy adoption in government and proposes novel applications like multi-level analysis and staffing efficiency improvements.

Findings

Differential privacy enables multiple analysis versions with varying privacy levels.

It can improve staffing efficiency in classified government applications.

Highlights the need for policy and technical solutions for government adoption.

Abstract

In this article, we seek to elucidate challenges and opportunities for differential privacy within the federal government setting, as seen by a team of differential privacy researchers, privacy lawyers, and data scientists working closely with the U.S. government. After introducing differential privacy, we highlight three significant challenges which currently restrict the use of differential privacy in the U.S. government. We then provide two examples where differential privacy can enhance the capabilities of government agencies. The first example highlights how the quantitative nature of differential privacy allows policy security officers to release multiple versions of analyses with different levels of privacy. The second example, which we believe is a novel realization, indicates that differential privacy can be used to improve staffing efficiency in classified applications. We hope that this article can serve as a nontechnical resource which can help frame future action from the differential privacy community, privacy regulators, security officers, and lawmakers.