69 citations · 194 across the 9 of their papers we have counts for
9 papers
Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making
Jakob Schoeffer, Maria De-Arteaga, Niklas Kuehl
In this work, we study the effects of feature-based explanations on distributive fairness of AI-assisted decisions, specifically focusing on the task of predicting occupations from…
"There Is Not Enough Information": On the Effects of Explanations on Perceptions of Informational Fairness and Trustworthiness in Automated Decision-Making
Jakob Schoeffer, Niklas Kuehl, Yvette Machowski
Automated decision systems (ADS) are increasingly used for consequential decision-making. These systems often rely on sophisticated yet opaque machine learning models, which do not…
On the Relationship Between Explanations, Fairness Perceptions, and Decisions
Jakob Schoeffer, Maria De-Arteaga, Niklas Kuehl
It is known that recommendations of AI-based systems can be incorrect or unfair. Hence, it is often proposed that a human be the final decision-maker. Prior work has argued that ex…
A Human-Centric Perspective on Fairness and Transparency in Algorithmic Decision-Making
Jakob Schoeffer
Automated decision systems (ADS) are increasingly used for consequential decision-making. These systems often rely on sophisticated yet opaque machine learning models, which do not…
Online Platforms and the Fair Exposure Problem Under Homophily
Jakob Schoeffer, Alexander Ritchie, Keziah Naggita +3
In the wake of increasing political extremism, online platforms have been criticized for contributing to polarization. One line of criticism has focused on echo chambers and the re…
Perceptions of Fairness and Trustworthiness Based on Explanations in Human vs. Automated Decision-Making
Jakob Schoeffer, Yvette Machowski, Niklas Kuehl
Automated decision systems (ADS) have become ubiquitous in many high-stakes domains. Those systems typically involve sophisticated yet opaque artificial intelligence (AI) technique…
Appropriate Fairness Perceptions? On the Effectiveness of Explanations in Enabling People to Assess the Fairness of Automated Decision Systems
Jakob Schoeffer, Niklas Kuehl
It is often argued that one goal of explaining automated decision systems (ADS) is to facilitate positive perceptions (e.g., fairness or trustworthiness) of users towards such syst…
A Study on Fairness and Trust Perceptions in Automated Decision Making
Jakob Schoeffer, Yvette Machowski, Niklas Kuehl
Automated decision systems are increasingly used for consequential decision making -- for a variety of reasons. These systems often rely on sophisticated yet opaque models, which d…
A Ranking Approach to Fair Classification
Jakob Schoeffer, Niklas Kuehl, Isabel Valera
Algorithmic decision systems are increasingly used in areas such as hiring, school admission, or loan approval. Typically, these systems rely on labeled data for training a classif…