Yves-Alexandre de Montjoye
Using Data while Protecting Privacy in the Digital Era
Yves-Alexandre de Montjoye is an Associate Professor at Imperial College London. He currently is a Special Adviser on AI and Data Protection to EC Justice Commissioner Reynders and a Parliament-appointed expert to the Belgian Data Protection Agency (APD-GBA). In 2018-2019, he was a Special Adviser to EC Competition Commissioner Vestager co-authoring the Competition Policy for the Digital Era report. His research has been published in Science and Nature Communications and has enjoyed wide media coverage (BBC, CNN, New York Times, Wall Street Journal, Harvard Business Review, etc.). His work on the shortcomings of anonymization has appeared in reports of the World Economic Forum, FTC, European Commission, and the OECD. Yves-Alexandre worked for the Boston Consulting Group and acted as an expert for both the Bill and Melinda Gates Foundation and the United Nations. He received his PhD from MIT in 2015 and obtained, over a period of 6 years, an M.Sc. from UCLouvain in Applied Mathematics, an M.Sc. (Centralien) from Centrale Paris, an M.Sc. from KULeuven in Mathematical Engineering as well as his B.Sc. in engineering from UCLouvain.
We live in a time when information about most of our movements and actions is collected and stored in real time. The availability of large-scale mobile phone, credit card, browsing history, etc data dramatically increase our capacity to understand and potentially affect the behavior of individuals and collectives.
The use of this data, however, raise legitimate privacy concerns. In this talk, I will discuss how traditional data protection mechanisms fail to protect people's privacy in the age of big data. More specifically, I will show how the mere absence of obvious identifiers such as name or phone number or the addition of noise are not enough to prevent re-identification and how sensitive information can often be inferred from seemingly innocuous data. I will then conclude by discussing some of socially positive uses of big data and solutions we are developing at Imperial College to allow large-scale behavioral data to be used while giving individual strong privacy guarantees.