Privacy-Enhancing Technologies, Sensitive Data-Sharing, and Privacy Protection

Tax returns and financial filings, health records, education records, and crime data are just some of detailed and highly sensitive data that governments have about people. Businesses also have huge archives of sensitive data, including consumer purchases, cellphone mobility traces, and video surveillance.

Today a tiny fraction of these data are released as open data or sold as de-identified data. The rest are locked up, unable to benefit society or promote new economic activity. Worse, much of that allegedly de-identified data can actually be re-identified.

Privacy Enhancing Technologies (PETs) use advanced mathematics and computational techniques to let organizations analyze and publish sensitive data while protecting the privacy or individuals and sensitive data from organizations. Although these techniques have existed for decades, they are increasingly being deployed by governments and businesses.

In this AI Cyber Lunch, Simson Garfinkel, Chief Scientist of BasisTech, LLC and Visiting Lecturer at Harvard Univeristy, will present  the case for PETs, explains popular PETs for a non-technical audience, and discusses the specific controversy of deploying differential privacy for the 2020 US Census.

Q&A to follow. Buffet-style lunch will be served.

Registration: RSVP required. A Harvard University ID is required for in-person attendance. All are welcome to attend on Zoom.

Recording: This seminar will NOT be recorded.

Accessibility: To request accommodations or who have questions about access, please contact Liz Hanlon (ehanlon@hks.harvard.edu) in advance of the session.