webinar

The Search for Anonymous Data – Yves-Alexandre de Montjoye, Imperial College London

30.06.2021 — 14:15

Second lecture of the seminar series ‘Sense & Sensibility of AI’

Flemish AI Academy, a collaboration between all the universities in Flanders

In times of big data, traditional techniques for data protection no longer suffice: even if identifiable information is left out, such as phone number or name, and even if noise is added, re-identification is still possible. Prof. de Montjoye of Imperial College London describes the problems, the possible solutions and the most recent developments.

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 behavioral data dramatically increases our capacity to understand and potentially affect the behavior of individuals and collectives.

The use of this data, however, raises legitimate privacy concerns. Anonymization is meant to address these concerns: allowing data to be fully used while preserving individuals’ privacy. In this talk, Prof. de Montjoye will first discuss how traditional data protection mechanisms fail to protect people’s privacy in the age of big data. More specifically, he 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. Second, de Montjoye will describe what he sees as a necessary evolution of the notion of data anonymization towards an anonymous use of data. He will then conclude by discussing some of the modern privacy engineering techniques currently developed to allow large-scale behavioral data to be used while giving individual strong privacy guarantees.

This lecture is part of the series "Sense & Sensibility of AI" of Vlaamse AI Academie and focuses on the different aspects of Ethics in AI, for Ph.D. students. Not only do we encourage them to be aware of the ethical challenges, but we also teach methodologies for identifying, assessing, and possibly solving ethical problems. We tackle topics such as bias and fairness, privacy, trustworthiness, and the balancing of technical, social, and legislative perspectives. For this series, the Flemish AI Academy works together with all Flemish universities.