In prior work [4], Anderson et al. introduced a new problem, the rankability problem, which refers to dataset's inherent ability produce meaningful ranking of its items. Ranking is fundamental data science task with numerous applications that include web search, mining, cybersecurity, machine learning, and statistical lea...

We propose introducing fairness constraints to one of the most famous multi-criteria decision-making methods, analytic hierarchy process (AHP). offer a solution that guarantees consistency while respecting legally binding in AHP pairwise comparison matrices. Through synthetic experiment, we generate matrices different sizes and ranges/levels initial parameters (i.e., ratio disparate impact). op...