1.1. What’s wrong with the nothing-to-hide argument?
Why should anyone care about privacy, especially people who feel they have nothing to hide?
One problem with this is that it assumes that there are no false positives. This assumes that strangers who make inferences about you based on your personal data – law enforcement, insurance companies, employers, etc. – are never wrong in their conclusions. Or if they are wrong, mistakes will be quickly and effortlessly resolved. Experience shows that every inference has some error rate, and that resolving errors can be painful or impossible. More on this here.
1.2. Does removing names make data deidentified?
Not at all. Removing names does little good if the data still contains the information needed to infer names. It can be surprisingly easy to identify people in data which has had obvious identifiers removed. For example, dates of service can sometimes be cross-referenced to identify individuals.
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