In AI governance, what does 'model lifecycle management' encompass?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because model lifecycle management is a comprehensive governance concept that covers all stages of a model's existence: business case and concept, data preparation, model development, validation, deployment, ongoing monitoring, model changes and retraining, and eventual decommissioning. Limiting it to training and testing (A) ignores most of the lifecycle.
Full explanation below image
Full Explanation
B is correct because model lifecycle management is a comprehensive governance concept that covers all stages of a model's existence: business case and concept, data preparation, model development, validation, deployment, ongoing monitoring, model changes and retraining, and eventual decommissioning. Limiting it to training and testing (A) ignores most of the lifecycle. Limiting it to post-deployment activities (C) ignores pre-deployment governance. Documentation and approval (D) are elements of lifecycle management but do not define it in full.