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Presented by: 
Josep Domingo-Ferrer (Universitat Rovira i Virgili )
Monday, December 5, 2016 - 14:40 to 15:10
INI Seminar Room 1

The explosion of big data opens such huge analytical and
inferential possibilities that they may allow modeling the world and predicting
its evolution with great accuracy.

The dark side of such data abundance is that it
complicates the preservation of individual privacy: big data largely feed on
the digital trace of our activities. Facing the tension between big data and
privacy, we find two extreme positions that strive for hegemony: on the one
side, the nihilists claim that it is delirious to try to maintain one's privacy
in the big data world, and that the best we can hope for is that our data are
not misused (if this means anything); on the other hand, the fundamentalists
propose privacy protection methods so drastic that their application would
destroy nearly all the analytical interest of big data.

We will survey these extreme positions and we will
describe a midway path, which we believe more balanced and desirable.

This path is based on identifying the utility and privacy
requirements of big data and trying to satisfy them through an evolution of the
statistical disclosure control methods developed in the last 40 years.

We will also briefly touch on transparent, local and
collaborative anonymization as ways to reduce the power of the data controller
in front of individual subjects.