[Keynote] Computational Privacy: The privacy bounds of human behavior — Yves-Alexandre de Montjoye (MIT Media Lab)
We're living in an age of big data, a time when most of our movements and actions are collected and stored in real time. Large-scale mobile phone, credit card, or browsing datasets dramatically increase our capacity to measure, 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 first show how the mere absence of obvious identifiers such as name or phone number is often not enough to prevent re-identification. I will then discuss how, as the use of this data progress, it will become increasingly important to consider whether sensitive information can be inferred from apparently innocuous data. Finally, I will discuss the impact of metadata on society and some of solutions we have been developing to allow metadata to be used in a privacy-conscientious way.
Yves-Alexandre de Montjoye is a Research Scientist at the MIT Media Lab (and was previously a postdoctoral researcher at Harvard IQSS). His research aims at understanding how the unicity of human behavior impacts the privacy of individuals in large-scale metadata datasets. (My work has been covered in The New York Times, BBC News, CNN, Wall Street Journal, Harvard Business Review, Le Monde, Die Spiegel, Die Zeit, El Pais, and in reports of the World Economic Forum, United Nations, OECD, FTC, and the European Commission, as well as in my talks at TEDxLLN and TEDxULg.)