Distributive Justice and Fairness Metrics in Automated Decision-making: How Much Overlap Is There? - Matthias Kuppler; Christoph Kern 001; Ruben L. Bach; Frauke Kreuter (CoRR, 2021)

Fairness in Algorithmic Profiling: A German Case Study. - Christoph Kern 001; Ruben L. Bach; Hannah Mautner; Frauke Kreuter (CoRR, 2021)

mcboost: Multi-Calibration Boosting for R. - Florian Pfisterer; Christoph Kern 001; Susanne Dandl; Matthew Sun; Michael P. Kim; Bernd Bischl (J. Open Source Softw., 2021)

mcboost: Multi-Calibration Boosting for R. - Florian Pfisterer; Christoph Kern 001; Susanne Dandl; Mathew Sun; Michael P. Kim; Bernd Bischl (Zenodo, 2021)

Uncertainty-aware predictive modeling for fair data-driven decisions. - Patrick Kaiser; Christoph Kern 001; David Rügamer (CoRR, 2022)

Humans versus machines: Who is perceived to decide fairer? Experimental evidence on attitudes toward automated decision-making. - Christoph Kern 001; Frederic Gerdon; Ruben L. Bach; Florian Keusch; Frauke Kreuter (Patterns, 2022)

Social impacts of algorithmic decision-making: A research agenda for the social sciences. - Frederic Gerdon; Ruben L. Bach; Christoph Kern 001; Frauke Kreuter (Big Data Soc., 2022)

Annotation Sensitivity: Training Data Collection Methods Affect Model Performance. - Christoph Kern 001; Stephanie Eckman; Jacob Beck; Rob Chew 001; Bolei Ma; Frauke Kreuter (EMNLP (Findings), 2023)

Ethnic Classifications in Algorithmic Decision-Making Processes. - Sofia Jaime; Christoph Kern 001 (EWAF, 2023)

When Small Decisions Have Big Impact: Fairness Implications of Algorithmic Profiling Schemes. - Christoph Kern 001; Ruben L. Bach; Hannah Mautner; Frauke Kreuter (EWAF, 2023)

What If? Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness. - Jan Simson; Florian Pfisterer; Christoph Kern 001 (EWAF, 2023)

Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness. - Jan Simson; Florian Pfisterer; Christoph Kern 001 (HHAI, 2023)

Everything, Everywhere All in One Evaluation: Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness. - Jan Simson; Florian Pfisterer; Christoph Kern 001 (CoRR, 2023)

Bridging the Gap: Towards an Expanded Toolkit for ML-Supported Decision-Making in the Public Sector. - Unai Fischer Abaigar; Christoph Kern 001; Noam Barda; Frauke Kreuter (CoRR, 2023)

Deciding the Future of Refugees: Rolling the Dice or Algorithmic Location Assignment? - Clara Strasser Ceballos; Christoph Kern 001 (EWAF, 2024)

Unveiling the Blindspots: Examining Availability and Usage of Protected Attributes in Fairness Datasets. - Jan Simson; Alessandro Fabris; Christoph Kern 001 (EWAF, 2024)

Ethnic Classifications in Algorithmic Fairness: Concepts, Measures and Implications in Practice. - Sofia Jaime; Christoph Kern 001 (FAccT, 2024)

Lazy Data Practices Harm Fairness Research. - Jan Simson; Alessandro Fabris; Christoph Kern 001 (FAccT, 2024)

One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisions. - Jan Simson; Florian Pfisterer; Christoph Kern 001 (FAccT, 2024)

Multi-CATE: Multi-Accurate Conditional Average Treatment Effect Estimation Robust to Unknown Covariate Shifts. - Christoph Kern 001; Michael P. Kim; Angela Zhou (CoRR, 2024)

The Missing Link: Allocation Performance in Causal Machine Learning. - Unai Fischer Abaigar; Christoph Kern 001; Frauke Kreuter (CoRR, 2024)

Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector. - Unai Fischer Abaigar; Christoph Kern 001; Noam Barda; Frauke Kreuter (Gov. Inf. Q., 2024)

Multi-Accurate CATE is Robust to Unknown Covariate Shifts. - Christoph Kern 001; Michael P. Kim; Angela Zhou (Trans. Mach. Learn. Res., 2024)

Connecting algorithmic fairness to quality dimensions in machine learning in official statistics and survey production. - Patrick Oliver Schenk; Christoph Kern 001 (AStA Wirtschafts und Sozialstatistisches Arch., 2024)

Preventing Harmful Data Practices by using Participatory Input to Navigate the Machine Learning Multiverse. - Jan Simson; Fiona Draxler; Samuel Mehr; Christoph Kern 001 (CHI, 2025)

Re-evaluating the role of refugee integration factors for building more equitable allocation algorithms. - Clara Strasser Ceballos; Marcus Novotny; Christoph Kern 001 (EWAF, 2025)

A Simulation Framework for Studying the Social Impacts of Algorithm-Based Refugee Matching. - Christoph Kern 001; Jakob Kappenberger; Frederic Gerdon; Clara Strasser Ceballos; Daria Szafran; Florian Rupp; Ruben L. Bach (EWAF, 2025)

Fares on Fairness: Using a Total Error Framework to Examine the Role of Measurement and Representation in Training Data on Model Fairness and Bias. - Patrick Oliver Schenk; Christoph Kern 001; Trent Buskirk (EWAF, 2025)

Location matching on shaky grounds: Re-evaluating algorithms for refugee allocation. - Clara Strasser Ceballos; Christoph Kern 001 (FAccT, 2025)

Correcting Annotator Bias in Training Data: Population-Aligned Instance Replication (PAIR). - Stephanie Eckman; Bolei Ma; Christoph Kern 001; Robert F. Chew; Barbara Plank; Frauke Kreuter (CoRR, 2025)

The Value of Prediction in Identifying the Worst-Off. - Unai Fischer Abaigar; Christoph Kern 001; Juan Carlos Perdomo (CoRR, 2025)

Fairness in Algorithmic Profiling: The AMAS Case. - Eva Achterhold; Monika Mühlböck; Nadia Steiber; Christoph Kern 001 (Minds Mach., 2025)

Algorithms for reliable decision-making need causal reasoning. - Christoph Kern 001; Unai Fischer Abaigar; Jonas Schweisthal; Dennis Frauen; Rayid Ghani; Stefan Feuerriegel; Mihaela van der Schaar; Frauke Kreuter (Nat. Comput. Sci., 2025)