Talk Title: Do machine learning systems meet the requirements of legal privacy standards?
Speaker: Kobbi Nissim, McDevitt Chair of Computer Science and affiliate professor at Georgetown University
Date: Wednesday, March 22, 2023 at 3:10 PM (ET)
Location: Zoom

Abstract:

Machine learning systems are widely used in the processing of personal information, and their use is growing at a rapid pace. While these systems bring many benefits, they also raise significant concerns about privacy. To mitigate such concerns, technical-mathematical frameworks such as differential privacy, and legal frameworks such as the EU’s General Data Protection Regulation (GDPR), have been introduced.

However, the relationship between privacy technology and privacy law is complex and the interaction between the two approaches exposes significant differences, making it challenging to reason whether systems do or do not provide the level of privacy protection as set by privacy law.

In this talk, we will review some of the gaps that exist between mathematical and legal approaches to privacy, and ongoing efforts to bridge them while maintaining legal and mathematical rigor.