When mitigating bias is unfair: multiplicity and arbitrariness in algorithmic group fairness

Natasa Krco, Thibault Laugel, Vincent Grari +2

Most research on fair machine learning has prioritized optimizing criteria such as Demographic Parity and Equalized Odds. Despite these efforts, there remains a limited understandi…