fairness constraint

Applying a constraint to an algorithm to ensure one or more definitions of fairness are satisfied. Examples of fairness constraints include: - Post-processing your model's output. - Altering the loss function to incorporate a penalty for violating a fairness metric. - Directly adding a mathematical constraint to an optimization problem.

Practitioners refer to fairness constraint when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.