Differential privacy is a formal mathematical formal mathematical framework for guaranteeing privacy protection when analyzing or releasing statistical data. Recently emerging from the theoretical computer science literature, differential privacy is now in initial stages of implementation and use in various academic, industry, and government settings.
This document is a primer on differential privacy. Using intuitive illustrations and limited mathematical formalism, this primer provides an introduction to dierential privacy for non-technical practitioners, who are increasingly tasked with making decisions with respect to dierential privacy as it grows more widespread in use. In particular, the examples in this document illustrate ways in which social science and legal audiences can conceptualize the guarantees provided by differetial privacy with respect to the decisions they make when managing personal data about research subjects and informing them about the privacy protection they will be afforded.