What is a Model Card?
A model card is a standardized documentation format that describes an AI model's intended use, performance characteristics, limitations, training data, ethical considerations, and evaluation results. It serves as a "nutrition label" for AI models — providing essential information for users and stakeholders to understand what the model can and cannot do.
Why It Matters
Model cards address the transparency gap in AI. Without documentation, users don't know what a model was trained on, where it performs well or poorly, or what biases it may contain. Model cards are increasingly required by regulations (EU AI Act mandates transparency for high-risk systems) and are standard practice at major AI labs. They enable informed model selection and responsible deployment.
How It Works
A model card typically includes:
1. Model details:
- Model name, version, type, architecture
- Developer organization and release date
- License and usage terms
2. Intended use:
- Primary use cases and target users
- Out-of-scope uses (what it should NOT be used for)
3. Training data:
- Description of training datasets
- Data collection methodology
- Known data limitations or biases