There are deep disagreements about the efficacy of de-identification to mitigate privacy risks. Some critics argue that it is impossible to eliminate privacy harms from publicly released data using de-identification because other available data sets will allow attackers to identify individuals through linkage attacks. Defenders of de-identification counter that despite the theoretical and demonstrated ability to mount such attacks, the likelihood of re-identification for most data sets remains minimal. As a practical matter, they argue most data sets remain securely de-identified based on established techniques.
There is no agreement regarding the technical questions underlying the de-identification debate, nor is there consensus over how best to advance the discussion about the benefits and limits of de-identification. The growing use of open data holds great promise for individuals and society, but also brings risk. And the need for sound principles governing data release has never been greater.
Selected authors from multiple disciplines including law, computer science, statistics, engineering, social science, ethics and business will present papers at this full-day programme.
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