1 INTRODUCTION

2 REAL-WORLD EXAMPLES OF ALGORITHMIC UNFAIRNESS

3 BIAS IN DATA, ALGORITHMS, AND USER EXPERIENCES

4 ALGORITHMIC FAIRNESS

5 METHODS FOR FAIR MACHINE LEARNING

6 CHALLENGES AND OPPORTUNITIES FOR FAIRNESS RESEARCH

7 CONCLUSION