2 Fairness and mitigating bias
Chapter 8 from Interpretable AI by Ajay Thampi
This chapter covers
- Identifying sources of bias in datasets
- Validating if machine learning models are fair using various fairness notions
- Applying interpretability techniques to identify the source of discrimination in machine learning models
- Mitigating bias using pre-processing techniques
- Documenting datasets using datasheets to improve transparency and accountability, and to ensure compliance with regulation