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A short document accompanying a trained AI model that describes its intended use, evaluation results, performance characteristics, limitations, and ethical considerations. Model cards were introduced by Google researchers in 2018 and have since become an industry standard for AI transparency. Major AI providers (Hugging Face, Google, Anthropic) 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.