An AI governance framework requires all deployed AI systems to maintain a 'model card.' Which information is MOST important to include in a model card for risk management purposes?
Select an answer to reveal the explanation.
Short Explanation
Model cards are transparency documents for risk management, so you need the intended use cases, known limitations, performance metrics across subgroups, and out-of-scope uses. That gives deployers and users what they need to avoid misapplication and understand failure modes.
Full Explanation
Model cards are transparency documents for risk management. The correct content is intended use cases to prevent misapplication, known limitations such as accuracy bounds and failure modes, performance metrics across subgroups to reveal differential performance, and out-of-scope uses. These give deployers and users the information needed for responsible governance. The data scientists' salaries, the cloud provider's hosting service level agreement, and names or contact details for training-data individuals are not standard model card elements for risk management.