most citedA Classification of Feedback Loops and Their Relation to Biases in Automated Decision-Making Systems

30 citations · 67 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CY2023★ 30 cited

A Classification of Feedback Loops and Their Relation to Biases in Automated Decision-Making Systems

Nicolò Pagan, Joachim Baumann, Ezzat Elokda +3

Prediction-based decision-making systems are becoming increasingly prevalent in various domains. Previous studies have demonstrated that such systems are vulnerable to runaway feed…

cs.LG2022★ 11 cited

Group Fairness in Prediction-Based Decision Making: From Moral Assessment to Implementation

Joachim Baumann, Christoph Heitz

Ensuring fairness of prediction-based decision making is based on statistical group fairness criteria. Which one of these criteria is the morally most appropriate one depends on th…

cs.CY2022★ 19 cited

Enforcing Group Fairness in Algorithmic Decision Making: Utility Maximization Under Sufficiency

Joachim Baumann, Anikó Hannák, Christoph Heitz

Binary decision making classifiers are not fair by default. Fairness requirements are an additional element to the decision making rationale, which is typically driven by maximizin…

cs.CY2022★ 5 cited

Distributive Justice as the Foundational Premise of Fair ML: Unification, Extension, and Interpretation of Group Fairness Metrics

Joachim Baumann, Corinna Hertweck, Michele Loi +1

Group fairness metrics are an established way of assessing the fairness of prediction-based decision-making systems. However, these metrics are still insufficiently linked to philo…

cs.CY2022★ 2 cited

A Justice-Based Framework for the Analysis of Algorithmic Fairness-Utility Trade-Offs

Corinna Hertweck, Joachim Baumann, Michele Loi +2

In prediction-based decision-making systems, different perspectives can be at odds: The short-term business goals of the decision makers are often in conflict with the decision sub…