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The canon · Data · AIS-3.5

Describe the de-identification or minimisation applied to consumer data before it is used in training.

This is one of the twenty-five questions a carrier reviewer sends a vendor, in the words an examiner uses. Below it: the answers that make a reviewer stop on this item, derived by running Vaulith's rules engine on an estate that gets everything wrong, and the free questions that reach it.

What stops a reviewer here

One finding reaches this item.

Will escalateR-PROVENANCE · degrades this item

No training-data provenance for MDL-001

The training corpus is described in engineering documentation but has never been approved as a record. Because the model is consumer-impacting, it is the one an examiner is most likely to name, and the gap sits on exactly that model.

To fix: Produce a provenance record covering sources, date range, volume, de-identification step, and approval.

How it is scored

Credit per verdict, times the weight.

A standard item carries weight 2. A pass earns 1.00 of it, a questioned answer 0.60, an escalated one 0.20 and a stop 0.00. An unanswered item earns nothing and still takes the citation penalty, so a profile cannot be improved by leaving an inconvenient question blank. The whole arithmetic is shown on the homepage and in every assessment.

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