Fairness and discrimination, PhD Course, #9 Mitigation, Pre-processing and In-processing

Finally, after defining (and quantifying) “group fairness“ and “individual fairness“, we can now start to discuss the idea of mitigating a possible discrimination. Here, we will see, how based on some data that were initially collected, and a model (a pricing model), it is possible to remove the discrimination in our pricing model. Biases everywhere As mentioned previously, insurance princing is based on the use of different datasets, at least one from “claims” and one from “underwriting”. And obviously, there might be biases in … <a href=“https://freakonometrics. …