  Differential privacy is a promising framework for addressing the privacy
concerns in sharing sensitive datasets for others to analyze. However
differential privacy is a highly technical area and current deployments often
require experts to write code, tune parameters, and optimize the trade-off
between the privacy and accuracy of statistical releases. For differential
privacy to achieve its potential for wide impact, it is important to design
usable systems that enable differential privacy to be used by ordinary data
owners and analysts. PSI is a tool that was designed for this purpose, allowing
researchers to release useful differentially private statistical information
about their datasets without being experts in computer science, statistics, or
privacy. We conducted a thorough usability study of PSI to test whether it
accomplishes its goal of usability by non-experts. The usability test
illuminated which features of PSI are most user-friendly and prompted us to
improve aspects of the tool that caused confusion. The test also highlighted
some general principles and lessons for designing usable systems for
differential privacy, which we discuss in depth.
