AIF-C01 - Responsible and secure AI - Section 5.1

Explain the development of responsible AI systems.

Recognise bias, fairness, and safety concerns, and the artefacts that address them, such as model cards that disclose intended use, limitations, training-data characteristics, and evaluation results.

Model cardsBias and fairnessResponsible AI

Practice question for this objective

Free sampleResponsible and secure AIeasy

A team is publishing a model card to accompany an image-classification model so that downstream adopters can judge whether it suits their own setting. They want the card to disclose the kind of information a model card is specifically intended to communicate. Which two pieces of information genuinely belong in the model card? Select TWO.

  • AThe cloud invoice and monthly hosting spend the team incurred while training the model on its accelerators.
  • BThe characteristics of the training data, including its sources, time range, and how representative it is of real conditions. Correct
  • CThe login credentials and access keys for the private repository where the model weights are stored.
  • DA marketing tagline asserting that the model is the most advanced classifier available on the market today.
  • EThe model's known limitations and evaluation results, including where its accuracy is measured to degrade. Correct
Recognise that a model card discloses training-data characteristics, intended use, limitations, and evaluation results so adopters can judge fitness before use. A model card is a transparency artefact written for downstream users. It describes what the model was trained on, how it was evaluated, and where its performance is known to break down, so adopters can decide whether it fits their context. Hosting costs, repository secrets, and marketing claims are not transparency content and do not belong in the card.

Why A is wrong: Tempting as project detail, but billing figures are an internal cost matter and are not part of what a model card discloses to adopters.

Why B is correct: Training-data characteristics are a core model card section so adopters can judge whether the data resembles their own population.

Why C is wrong: This looks like provenance, but secrets must never be published and are a security matter rather than transparency content.

Why D is wrong: A slogan is promotional filler, whereas a model card is meant to give factual, checkable disclosures rather than sales claims.

Why E is correct: Documenting limitations and evaluation outcomes lets adopters see where the model is reliable and where it fails before they use it.

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