… assessment using different metrics. This paper provides an overview of the actual FAIR
assessment tools and metrics … 20 relevant FAIR assessment tools and 1180 relevant metrics were …

… method ie, a metric, for assessing and scoring to which … ”, “FAIR” or even “FAIRer” than a
certain threshold or another resource. … assessment grid to enable researchers and other data …

… This article proposes a novel metric assessment tactic that can clarify and simplify future …
the biased model to make the models fairer. We will use those metric values based on the three …

… alternative algorithms to be fairer to protected groups. … metrics can structure these judgments
so that the issues can be faced squarely.Assessments of algorithms appear to be about data…

… , allowing for assessing unfairness and bias in their data, and … to make a classification model
fairer by removing bias only in … in exchange for improved fairness metrics, without requiring …

… fairest algorithm. On the contrary, and as reported in Table 4 (for the case of Argmax policy),
SVM was the overall fairest … measured by Brier score on the test data repetitions. In all cases, …

… Fairlearn supports a wide range of fairness metrics for assessing a model’s impacts on …
toward fairer AI systems requires input from a breadth of perspectives, ranging from data scientists…

… program; in Chapter 2 we introduce a Data Imbalance-based Risk Assessment Approach
and … Note that to assess the balance in data, we will refer to balance measures, metrics of …

… and fairness metrics intending to assess the quality of … We apply fairness metrics across
all the data splits of CIFAR10, as … the fairest algorithm according to the other fairness metrics. …

… metrics to assess specific solutions with respect to the way the features they provide enable
each of the FAIREST … For this reason, we propose below the FAIREST principles that extend …