The Department of Mathematical and Data Sciences will host this discussion on OpenDP from 5-6:30 p.m. Tuesday (April 18) in White Hall, Room G09.
Learning the causal structure of the world is a central goal of many disciplines. While we increasingly have data at scale to answer questions, the data can be fiercely private and distributed across data holders who should not share or leak private information.
Speaker James Honaker, chief privacy officer at OpenDP, will give a simple introduction to differential privacy and discuss how this can be combined with other privacy enhancing technologies — such as homomorphic encryption, secure multiparty computation or trusted execution environments — to provide private building blocks for causal reasoning that work at internet scale.