There are several different mathematical fairness checking and balancing methods available. Some of these should be added to MLOps.
Previous suggestion of this was made by Laurence Jackson.
"https://ai-fairness-360.org/
AI Fairness 360 is an open-source toolkit for measuring and compensating for data bias in AI.
It looks like its got a lot of potential for us to understand our data/model biases. They have a load of example notebooks on their GitHub demonstrating how we could use it.
e.g.
https://github.com/Trusted-AI/AIF360/blob/master/examples/tutorial_credit_scoring.ipynb
https://github.com/Trusted-AI/AIF360/blob/master/examples/tutorial_medical_expenditure.ipynb "