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pluralistic@mamot.fr ("Cory Doctorow") wrote:
Indeed, it appears that there may be *no* way to truly de-identify a data-set:
https://pursuit.unimelb.edu.au/articles/understanding-the-maths-is-crucial-for-protecting-privacy
Which is a serious bummer, given the potential insights to be gleaned from, say, population-scale health records:
https://www.nytimes.com/2019/07/23/health/data-privacy-protection.html
It's clear that de-identification is not fit for purpose when it comes to these data-sets:
https://www.cs.princeton.edu/~arvindn/publications/precautionary.pdf
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