  Increasingly, scholars seek to integrate legal and technological insights to
combat bias in AI systems. In recent years, many different definitions for
ensuring non-discrimination in algorithmic decision systems have been put
forward. In this paper, we first briefly describe the EU law framework covering
cases of algorithmic discrimination. Second, we present an algorithm that
harnesses optimal transport to provide a flexible framework to interpolate
between different fairness definitions. Third, we show that important normative
and legal challenges remain for the implementation of algorithmic fairness
interventions in real-world scenarios. Overall, the paper seeks to contribute
to the quest for flexible technical frameworks that can be adapted to varying
legal and normative fairness constraints.
