4 papers
Differential Perspectives: Epistemic Disconnects Surrounding the US Census Bureau's Use of Differential Privacy
danah boyd, Jayshree Sarathy
When the U.S. Census Bureau announced its intention to modernize its disclosure avoidance procedures for the 2020 Census, it sparked a controversy that is still underway. The move…
Statistical Imaginaries, State Legitimacy: Grappling with the Arrangements Underpinning Quantification in the U.S. Census
Jayshree Sarathy, danah boyd
Over the last century, the adoption of novel scientific methods for conducting the U.S. census has been met with wide-ranging receptions. Some methods were quietly embraced, while…
"Having Confidence in My Confidence Intervals": How Data Users Engage with Privacy-Protected Wikipedia Data
Harold Triedman, Jayshree Sarathy, Priyanka Nanayakkara +4
In response to calls for open data and growing privacy threats, organizations are increasingly adopting privacy-preserving techniques such as differential privacy (DP) that inject…
"I inherently just trust that it works": Investigating Mental Models of Open-Source Libraries for Differential Privacy
Patrick Song, Jayshree Sarathy, Michael Shoemate +1
Differential privacy (DP) is a promising framework for privacy-preserving data science, but recent studies have exposed challenges in bringing this theoretical framework for privac…