#BigData & #Datascience Don’t let it be another faith based #opinion riddled debate. Any of these sound familiar?

Any of these resonate with you? Then read on!

Specifically, we argue that:

1. There is no known effective method to anonymize location data, and no evidence that it’s meaningfully achievable.

2. Computing re-identification probabilities based on proof-of-concept demonstrations is silly.

3. Cavoukian and Castro ignore many realistic threats by focusing narrowly on a particular model of re-identification.

4. Cavoukian and Castro concede that de-identification is inadequate for high-dimensional data. But nowadays most interesting datasets are high-dimensional.

5. Penetrate-and-patch is not an option.

6. Computer science knowledge is relevant and highly available.

7. Cavoukian and Castro apply different standards to big data and re-identification techniques.

8. Quantification of re-identification probabilities, which permeates Cavoukian and Castro’s arguments, is a fundamentally meaningless exercise.



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