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It's not as simple as that. What's the k-anonymity on your datasets? I'd be mightily impressed if anyone at your company had ever calculated it, yet 'pseudonymi
by roel_v 9y ago
It's not as simple as that. What's the k-anonymity on your datasets? I'd be mightily impressed if anyone at your company had ever calculated it, yet 'pseudonymisation' is meaningless without quantitative assessments of its results.
From what I've seen in research, when you get an 'anonymized' dataset from e.g. a government institute, hospital or school, someone will have replaced the names in the 'Name' column with 'Subject 1', 'Subject 2' and so on, and if you're lucky they'll have removed the DoB column. How many people are there in the average organization who are even qualified to have an opinion on whether a dataset is sufficiently anonymous for a certain purpose?
The first few years of GDPR lawsuits are going to be about obvious things, hopefully we'll get to see a few more interesting ones about stuff like this once that basic stuff is settled :)
- saltcured 9y agoAnd, if you are interested in ethics rather than loopholes, things like k-anonymity are not properties of datasets but of datasets with respect to an assumed corpus of other information. You have to consider how this new data could be integrated with other previous or future data releases and what level of anonymity remains after that integration. Eventually, if you work this analysis through sincerely enough, you will probably abandon all hope of maintaining k-anonymity in real data management practices. Then, you face your real ethical decision as you either drastically restrict the data or turn to lawyers and loopholes to assuage your guilt as you continue with the naive levels of protection demanded by your application and organization...