Data minimization
The principle of collecting and keeping only the data you strictly need. It is the best answer when erasing is impossible.
Article 5(1)(c) of the GDPR, Regulation (EU) 2016/679 of April 27, 2016, applicable since May 25, 2018, requires personal data to be “adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed”. That is the data minimization principle, and point (e) extends it over time by limiting storage. Article 17 gives a right to be forgotten, but erasure becomes approximate once data has been absorbed into models. Minimization answers that problem upstream: the best protection against an erasure request is never to have absorbed the data it would target. It goes hand in hand with pseudonymization, aggregation and privacy-preserving learning techniques that limit the personal footprint in the model. It marks a shift in data governance, from content to life cycle: compliance is designed in from the start rather than resting on the ability to delete after the fact.
Textbook case: rather than training its model on named data it may later have to erase, an insurer aggregates and pseudonymizes them upstream, reducing its exposure to the right to be forgotten.
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