Your model was fair at launch and biased six months later. How do you monitor fairness continuously?

Fairness is a property of the model and the data it meets, so it drifts even when the weights never change. Treating it as a monitoring problem exposes three things a one-off audit never has to solve: noisy small slices, multiple comparisons, and labels that arrive months late.

Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.