A model card is a standardized documentation artifact for machine learning models that discloses intended use, performance characteristics, training data provenance, limitations, and ethical considerations. Parameters: (1) structured sections covering model details and performance metrics, (2) demographic or conditional disaggregation where relevant, (3) explicit statements of known limitations and failure modes, (4) governance metadata (authoring team, date, version). Persistence: published as a human-readable document (PDF, HTML, markdown) alongside model repositories, maintained through model iteration cycles, and enforced by organizational policy or regulatory requirement. [formal: model_cardarium | substrate: behavior | horizon: a life | explicit: yes | epoch: 0.01]
Accepted ontology entry
model-card
A model card is a standardized documentation artifact for machine learning models that discloses intended use, performance characteristics, training data provenance, limitations, and ethical considerations. Parameters: (1) structured secti…
Definition
Why it is in scope
A human-made document artifact that standardizes the disclosure of machine learning model properties: intended use, performance characteristics across demographics or conditions, training data provenance, limitations, and ethical considerations. Originated in responsible-AI practice (Google's model cards initiative) and adopted as a governance tool across the ML ecosystem.
Names and aliases
- model-carden · CANONICAL
Relations from this entry
- cmrz2cszc02s2ekkxlce5xklsINSTANCE_OF →
A model card IS a specific kind of documentation — a standardized artifact that discloses ML model properties. A competent speaker calls it 'a type of documentation.' Law 9: INSTANCE_OF against nearest kind.
- cmrz2cszc02s2ekkxlce5xklsSERVES →
Model cards are built specifically to serve documentation needs — they document ML model behavior, training data, intended use, and evaluation results. Their designed purpose is to serve the documentation of machine learning systems.
- cmsaawx5r038n7skq7o1jqh2wSERVES →
Model cards are explicitly designed to provide transparency about AI/ML models — their intended use, limitations, training data, and evaluation results. The purpose is transparency: remove model cards and that structured transparency disappears.
Relations to this entry
No accepted relations in this direction.
Record identity
- Created
- Aug 13, 2026, 10:28 PM UTC
- Content hash
- 77259a269493ba9eb50554d689e24a18a2a4fca64b2a578e1887dcf525ce387d