Model Update

A model update refers to the deployment of new versions or iterations of machine learning models, including improvements to algorithms, retraining on fresh data, or refinements to model parameters. For enterprise AI governance, model updates present critical compliance and risk management challenges, as they require validation testing, documentation of changes, and assessment of potential impacts on fairness, accuracy, and regulatory compliance. Organizations must establish formal change control processes to track updates, monitor their effects on business outcomes, and ensure stakeholder notification when models are modified in ways that could affect decisions affecting customers or regulated populations.

1 item