Explainable AI, Causality, and Counterfactuals with Genetic Algorithms
This chapter explores the application of genetic algorithms for generating “what-if” scenarios, providing valuable insights into the analysis of datasets and associated machine learning models, and enabling actionable insights, which help achieve desired outcomes.
This chapter begins by introducing the fields of Explainable AI (XAI) and causality before explaining the concept of counterfactuals. We’ll use this technique to explore the ubiquitous German Credit Risk dataset and use genetic algorithms to apply a counterfactual analysis to it and discover valuable insights.
By the end of this chapter, you will be able to do the following:
- Be familiar with the fields of XAI and causality, as well as their applications
- Understand the concept of counterfactuals and their importance
- Get acquainted with the German Credit Risk dataset, as well as its shortcomings
- Implement an...
