Model Documentation

Technical and non-technical descriptions (e.g., model cards) that disclose an AI system's purpose, training data characteristics, performance metrics, limitations, and audit trails to enable transparency, oversight and reproducibility. The policy requires publication of non-sensitive model documentation, particularly for systems used in public administration.

The set of reproducible artefacts—such as data descriptions, training logs, evaluation results and model cards—required by MAIC for conformity assessment, provenance tracking and transparency of AI models used in consortium activities.

Structured technical and explanatory documentation that records a model's architecture, training procedures, datasets used, performance metrics, limitations, intended use cases, and maintenance/monitoring plans to enable oversight, reproducibility and explainability.

Model documentation refers to structured records (e.g., model cards, datasheets) that describe datasets, training processes, evaluation metrics, risk assessments and mitigation measures for AI models, intended to ensure transparency, enable audits, and support legal and ethical compliance—particularly for publicly funded models.