Why is behavioral data so hard to anonymize? What is k-anonymity and why is it so hard to apply it to geolocation data? Is differental privacy the holy grail? What are the philosophical and technical limitations of differential privacy? Yves-Alexandre de Montjoye, the prominent scientist from the Imperial College of London and MIT attempts to answer all of these questions in the episode. On top of these crucial questions and definitions, you can learn more about:
  • why event level differential privacy fails to protect location data,
  • what are meaningless privacy guarantees and what should we do about them,
  • what's the difference between the theory and the practice of data privacy,
  • what is the definition of synthetic data,
  • the use cases and limitation of synthetic data,
  • about GDPR and the future of guidance on data anonymization.
If you are interested in the future of data privacy legislation, make sure you also listen to our previous episode on the transatlantic data privacy framework with Scott Marcus from Bruegel!