AI Vocabulary · 08 Rules & Responsibility

What is Model Card?

A short document that comes with an AI model and states what it is for, how it was tested and where it falls short.

Intermediate

A model card is like a package insert for an AI model. It describes what the model is intended for, how it was evaluated, how well it performs for different groups and conditions, and what it should not be used for. Many model makers publish one with each release. Some publish longer "system cards" for complete products; their content is not standardised.

The idea comes from a 2018 paper by Margaret Mitchell, Timnit Gebru and colleagues at Google. They proposed reporting performance broken down by demographic, cultural and other groups, so that weaknesses for some people would not stay hidden behind an average.

The EU AI Act goes further for general-purpose AI models. Their providers must keep technical documentation, including the training and testing process and evaluation results, with at least the details listed in Annex XI: intended tasks, architecture and number of parameters, licence, training data and its origin, computing resources and energy use (Article 53). This documentation goes to authorities on request, not automatically to the public. A model card is a voluntary format; the Act does not use the term.

Why it matters for you

The model card is the quickest way to see what a model was built and tested for, and where its makers themselves see limits and bias.

Own it

Read the model card before you build on a model, and keep a copy with your records. If you build or adapt models yourself, write a short card for each: purpose, data, tests, limits.

Related