Is it possible to make a verifiable data provenance log for datasets used for machine learning? Sort of a hash that would confirm that a collection of datasets were actually used to train a given model.
Example. We have a collection of 10 datasets: D1-D10. Let's say D1, D5 and D6 were used for training. The task is to save some kind of a "provenance hash" that would certify that no other dataset was used, except for D1, D5, D6. In other words, it should be verifiable that:
- D1, D5 and D6 were actually used,
- D2, D3, D4, D7-D10 were not used,
- no other data was also used.
The last one is hard, so maybe this statement should be probabilistic.