Platform and Model Design for Responsible AI

8

Fairness in Model Optimization

Machine Learning (ML) has made massive strides in recent years, with applications in everything from finance to healthcare. However, these systems can often be opaque and biased against certain groups of people. In order for ML to live up to its potential, we must ensure that it is fair and unbiased.

In Chapter 7, we discussed the concept of fairness in the context of data generation. In this chapter, we will cover different optimization constraints and techniques that are essential to optimizing and obtaining fair ML models. The focus of this chapter is to enlighten you about new custom optimizers, unveiled by research that can serve to build fair supervised, unsupervised, and semi-supervised ML models. In a ...