Stairway to Fairness: Connecting Group and Individual Fairness
Authors: name: Theresia Veronika Rampisela, name: Maria Maistro, name: Tuukka Ruotsalo, name: Falk Scholer, name: Christina Lioma

Fairness in recommender systems (RSs) is commonly categorised into group
fairness and individual fairness. However, there is no established scientific
understanding of the relationship between the two fairness types, as prior work
on both types has used different evaluation measures or evaluation objectives
for each fairness type, thereby not allowing for a proper comparison of the
two. As a result, it is currently not known how increasing one type of fairness
may affect the other. To fill this gap, we study the relationship of group and
individual fairness through a comprehensive comparison of evaluation measures
that can be used for both fairness types. Our experiments with 8 runs across 3
datasets show that recommendations that are highly fair for groups can be very
unfair for individuals. Our finding is novel and useful for RS practitioners
aiming to improve the fairness of their systems. Our code is available at:
https://github.com/theresiavr/stairway-to-fairness.