Acceptance Criteria -Accuracy, Bias, and Fairness

From The Foundation for Best Practices in Machine Learning
Technical Best Practice Guideline > Model Decision-Making > Acceptance Criteria -Accuracy, Bias, and Fairness

Acceptance Criteria - Accuracy, Bias, and Fairness

Control

Document and define clear, narrow accuracy goals and metrics that manage the tradeoff of accuracy and explainability. Document and define the Model requirements needed to meet the Fairness & Non-Discrimination goals, as discussed more thoroughly and technically in Section 11 - Fairness & Non-Discrimination.


Aim

To (a) ensure appropriate accuracy, bias and fairness metrics for Model(s); and (b) highlight associated risks that might occur in the Product Lifecycle.


Additional Information