Tools are starting to roll out to help with fairness and bias detection in machine learning. Some of it is targeted at mitigation and other parts are true efforts to remediate. Really the most important part of the process is the recognition of fairness as a concept. You have to begin to understand what bias can mean within machine learning to start working on mitigation and remediation. Ensuring the process is definable and repeatable creates the potential for quality.