A model card summarizing intended use: Under III.C.1 | AIGP
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A model card summarizing intended use: Under III.C.1, which readiness artifact fits this need?

AIGP Understanding How to Govern AI Development Medium

A model card is the readiness artifact that summarizes intended use, performance across conditions, and limitations for deployers.

The question

As a computer-vision model nears release, deployers need a concise document describing its intended use, performance across conditions, and known limitations so they can decide where to apply it safely. Under III.C.1, which readiness artifact fits this need?

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  1. A model card summarizing intended use, evaluation results across conditions, and known limitations, so deployers can judge appropriate application. ✓
    A model card is precisely the release-readiness artifact conveying intended use, performance, and limitations to guide deployers' decisions.
  2. A software license agreement setting out the permitted commercial uses and liability terms, so deployers understand the legal conditions attached to the system.
    A license governs legal terms of use, not the model's performance and limitations that deployers need to judge safe application.
  3. A network architecture diagram of the serving infrastructure, so deployers can see how requests are routed and where the model is hosted in production.
    An infrastructure diagram describes hosting, not the model's intended use, performance, or limitations that a readiness artifact must convey.
  4. A source-code style guide followed by the engineering team, so deployers can confirm the codebase was written to consistent internal quality conventions.
    A style guide reflects code conventions and is irrelevant to communicating the model's intended use and limitations to deployers.
The trap
Substituting legal, infrastructure, or code documents for the model card that communicates use and limitations.

How to remember it

A model card is the readiness artifact that summarizes intended use, performance across conditions, and limitations for deployers.

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