Data Audit
An audit mechanism in AI compliance processes that examines training data sources, licenses, PII and similar factors. It verifies the input data itself rather than model behavior.
Timeline (last 90 days)
Data review verifies that the input documents do not contain the content of concern and says nothing about the function that maps inputs to weights, yet that is exactly where the coupling happens.
Provenance tracking, PII interception, and avoiding training on the same eval set are real controls, but they control inputs, not outputs.
Treating "behavior is coupled" as an excuse to not review data at all would be worse than the misconception it replaces.
All Facts (3)
Data review verifies that the input documents do not contain the content of concern and says nothing about the function that maps inputs to weights, yet that is exactly where the coupling happens.
50%UnverifiedProvenance tracking, PII interception, and avoiding training on the same eval set are real controls, but they control inputs, not outputs.
50%UnverifiedTreating "behavior is coupled" as an excuse to not review data at all would be worse than the misconception it replaces.
50%