A 15min Introduction to Differential Privacy

This talk provides an accessible introduction to the core ideas behind differential privacy through the lens of simple, intuitive examples. Starting from the classical randomized response mechanism, we show how privacy and accuracy trade off and how this motivates the formal ε-DP framework. I then present the Laplace mechanism, explaining its accuracy guarantees and why it offers significantly better utility than basic randomized response. The goal is to give a clear, self-contained overview of the principles that underpin modern privacy-preserving data analysis.