Colorado ADMT rules: hearing and last day for written comments · Oct 26, 2026 · See what changes
A short document accompanying a trained AI model that describes its intended use, evaluation results, performance characteristics, limitations, and ethical considerations. Model cards were proposed in the 2018 paper 'Model Cards for Model Reporting' by Margaret Mitchell, Timnit Gebru and colleagues and are now widely used for AI transparency. Many providers publish model cards for their models. For teams deploying AI, reading the model card helps identify known failure modes, bias characteristics, and use cases the model was not designed for, all relevant to risk assessment.
Why this matters for your team
Read the model card before you build a product on a foundation model. It tells you what the model was tested on, where it performs poorly, and what use cases it was not designed for — all of which directly affect your risk profile and liability exposure.