  This paper proposes a method for measuring fairness through equality of
effort by applying algorithmic recourse through minimal interventions. Equality
of effort is a property that can be quantified at both the individual and the
group level. It answers the counterfactual question: what is the minimal cost
for a protected individual or the average minimal cost for a protected group of
individuals to reverse the outcome computed by an automated system? Algorithmic
recourse increases the flexibility and applicability of the notion of equal
effort: it overcomes its previous limitations by reconciling multiple treatment
variables, introducing feasibility and plausibility constraints, and
integrating the actual relative costs of interventions. We extend the existing
definition of equality of effort and present an algorithm for its assessment
via algorithmic recourse. We validate our approach both on synthetic data and
on the German credit dataset.
