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Overview
Differential privacy is a principled approach to sharing insights about groups, without revealing personal data about individuals. In this talk, we will explain what differential privacy is about, provide a high-level intuition of how it works, and explain what kind of problems it can solve. We will then present a case study from our work with the Internal Revenue Service, to provide a concrete example of a real-world deployment of this approach. We will then conclude by giving a brief overview of our work towards making it easier for anyone to use and deploy differential privacy.
Moderator
R. Jason Cronk – President, Institute of Operational Privacy Design
With over two decades of experience in principle and trust consulting, R. Jason Cronk is a seasoned privacy engineer, developer, lawyer, author of the IAPP textbook “Strategic Privacy by Design,” Section Leader of the IAPP’s Privacy Engineering Section, and founder and president of the Institute of Operational Privacy Design, a non-profit organization of privacy professionals which seeks to define and drive the adoption of common and comprehensive standards to protect individuals’ privacy.
His knowledge and involvement reaches across the spectrum as an active member of the academic, engineering, legal and professional privacy communities and a pioneering voice in the development of privacy by design. Whether it is writing books, developing models and frameworks, or training companies and individuals alike, he is tirelessly advocating for privacy across the globe.
Speaker/s
Damien Desfontaines – Senior Scientist, Tumult Labs
Damien Desfontains is a senior scientist at Tumult Labs, a startup focusing on differential privacy. Before that, he was leading the anonymization consulting team at Google. In 2020, he defended my PhD thesis at ETH Zürich, where worked on part-time in the Information Security Group, under the supervision of David Basin. Previously, he studied at the École normale supérieure, where he completed a Master's degree in mathematical logic and theoretical computer science called the LMFI.
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