1 Introduction

2 Fairness in Machine Learning: Key Methodological Components

3 Measuring Fairness and Bias

4 Binary Classification Approaches

5 Beyond Binary Classification

6 Current Platforms

7 Concluding Remarks: The Fairness Dilemmas