What document should be created to provide standardized information about an AI model?

The choice of model cards or facts sheets as the correct answer is grounded in their purpose and function within AI governance. Model cards are a type of documentation designed specifically to provide standardized and concise information about an AI model's characteristics, including its intended use, performance metrics, and any limitations or risks associated with deploying the model.

These documents can help stakeholders understand how the model operates, its performance boundaries, the dataset it was trained on, and ethical considerations. With the growing emphasis on transparency and accountability in AI systems, standardizing this information through model cards enables better communication among developers, users, and regulators.

Risk assessment reports, though valuable, focus primarily on identifying, assessing, and mitigating risks associated with the deployment of AI systems, rather than providing a comprehensive overview of the model itself. User manuals serve as guides for end-users on how to interact with a system but do not encapsulate the essential characteristics and evaluation of the AI model. Algorithm blueprints might delve into the technical details of the algorithm's design and function, but they do not generally offer the holistic overview regarding performance and operational context that model cards aim to deliver.

Thus, model cards are crucial for fostering an understanding of AI systems, ensuring informed decision-making, and facilitating responsible AI governance