“K-anonymity was born out of a desire both to quantify the re-identifiability of a dataset, and to balance the usefulness of de-identified people data and the privacy of the people whose data is being used.”
Researchers have also shown recently that many high-dimensional datasets (mobile phone metadata, online ratings, etc.) cannot be de-identified without loosing all their utility [1, 2, 3]. In that case, there is no distinction between quasi-identifiers and sensitive data. All the information in the dataset can be used to identify an individual. De-identification algorithms such as the one used here make strong assumptions that the data collector knows which information can and cannot be used to re-identify individuals.
[1] https://www.cs.utexas.edu/~shmat/shmat_oak08netflix.pdf