One working control on the engineering side of AI governance.
Summary: Treat the model card and data card not as launch documentation written once, but as
structured evidence regenerated from the pipeline, so that transparency documents describe the system as
it is now and feed the assurance layer.
Model Card as EvidenceThe model card is generated from real training and eval outputs, checked against a schema at one gate, and attached to the release as control evidence. A hand-written card is documentation; a generated, validated one is a control. Generated from the Body of Knowledge.Open interactive diagram (opens in a new tab)
Convert transparency documentation from a static PDF into a versioned artefact that is both
human-readable and machine-consumable, and that counts as control evidence.
A model card written once decays into fiction as the model, prompts and datasets change. A card that is
not regenerated cannot be trusted as evidence and misleads the very auditor it was meant to satisfy.
Template the card and populate it from the pipeline: intended use, evaluation results (from the Eval
Gate), datasets (from the AIBOM), known limitations and owner. Regenerate on each significant change and
version it with the model. Store the card as structured data so it can be both read by a person and
consumed by the assurance layer.
Transparency stays true and doubles as evidence. The cost is templating and pipeline wiring, and
agreeing what “significant change” triggers a regeneration.