Research

2024

• Schenk, P. O. and Kern, C. (2024). Connecting Algorithmic Fairness to Quality Dimensions in Machine Learning in Official Statistics and Survey Production. arXiv. https://arxiv.org/abs/2402.09328
• Jaime, S. and Kern, C. (2024). Ethnic Classifications in Algorithmic Fairness: Concepts, Measures and Implications in Practice. In the 2024 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’24). Association for Computing Machinery, New York, NY, USA, 237–253. https://doi.org/10.1145/
  3630106.3658902.
• Simson, J., Fabris, A. and Kern, C. (2024). Lazy Data Practices Harm Fairness Research. In the 2024 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’24). Association for Computing Machinery, New York, NY, USA, 642–659. https://doi.org/10.1145/3630106.3658931.
• Simson, J., Pfisterer, F. and Kern, C. (2024). One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisions. In the 2024 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’24). Association for Computing Machinery, New York, NY, USA, 1305–1320. https://doi.org/10.1145/3630106.3658974
• Fischer-Abaigar, U., Kern, C. and Kreuter, F. (2024). The Missing Link: Allocation Performance in Causal Machine Learning. Humans, Algorithmic Decision-Making and Society: Modeling Interactions and Impact, co-located with ICML 2024. https://arxiv.org/abs/2407.10779.
• Szafran, D. and Bach, R. L. (2024). The Human Must Remain the Central Focus: Subjective Fairness Perceptions in Automated Decision-Making. Minds and Machines, 34(3), 24. https://doi.org/10.1007/s11023-024-09684-y
• F. Rupp, A. Puddu, C. Becker-Asano and K. Eckert. (2024). It might be balanced, but is it actually good? An Empirical Evaluation of Game Level Balancing. 2024 IEEE Conference on Games (CoG), Milan, Italy, 2024, pp. 1-4, https://doi.org/10.1109/CoG60054.2024.10645642.
• F. Rupp and K. Eckert. (2024). G-PCGRL: Procedural Graph Data Generation via Reinforcement Learning. 2024 IEEE Conference on Games (CoG), Milan, Italy, 2024, pp. 1-8, https://doi.org/10.1109/CoG60054.2024.10645633.
• F. Rupp and K. Eckert. (2024) GEEvo: Game Economy Generation and Balancing with Evolutionary Algorithms. 2024 IEEE Congress on Evolutionary Computation (CEC), Yokohama, Japan, 2024, pp. 1-8, https://doi.org/10.1109/CEC60901.2024.10612054
• Rupp F., Eberhardinger M., and Eckert K. (2024). Simulation-Driven Balancing of Competitive Game Levels with Reinforcement Learning, IEEE Transactions on Games, pp. 1–11, 2024.  https://doi.org/
  10.1109/TG.2024.3399536
• Rupp F., Schnabel B., and Eckert K. (2024). Implementing Data Workflows and Data Model Extensions with RDF-star. The Electronic Library (TEL), Emerald Publishing Limited. https://doi.org/10.1108/EL-04-2023-0102

2023

• Bach, R. L., Kern, C., Mautner, H., and Kreuter, F. (2023). The Impact of Modeling Decisions in Statistical Profiling. Data & Policy 5, E32. https://doi.org/10.1017/dap.2023.29
• Rupp F., Eberhardinger M., and Eckert K. (2023). Balancing of competitive two-player Game-Levels with Reinforcement Learning. IEEE Conference on Games (CoG). https://doi.org/10.1109/CoG57401.2023.10333248
• Fischer Abaigar, U., Kern, C., Barda, N., Kreuter, F. (2023). Bridging the Gap: Towards an Expanded Toolkit for ML-Supported Decision-Making in the Public Sector. arXiv. https://arxiv.org/abs/2310.19091
• Szafran D.  and Bach R. L. (2023): The human must remain the central focus: Subjective fairness perceptions in algorithmic decision-making. ESRA 2023 Conference.

2022

• Kern C., Gerdon F., Bach R. L., Keusch F., and Kreuter F. (2022). Humans versus Machines: Who is Perceived to Decide Fairer? Experimental Evidence on Attitudes Toward Automated Decision-Making. Patterns. https://doi.org/10.1016/j.patter.2022.100591
• Gerdon F., Bach R. L., Kern C., and Kreuter, F. (2022). Social Impacts of Algorithmic Decision-Making: A Research Agenda for the Social Sciences. Big Data & Society. https://doi.org/10.1177/20539517221089305
• Kappenberger J., Theil K. and Stuckenschmidt, H. (2022). Evaluating the Impact of AI-Based Priced Parking with Social Simulation. In: Hopfgartner, F., Jaidka, K., Mayr, P., Jose, J., Breitsohl, J. (eds) Social Informatics. SocInfo 2022. Lecture Notes in Computer Science, vol 13618. Springer, Cham. https://doi.org/10.1007/978-3-031-19097-1_4
• Rupp F., Schnabel B., and Eckert K. (2022). Easy and Complex: New Perspectives for Metadata Modeling Using RDF-Star and Named Graphs. In: Villazón-Terrazas, B., Ortiz-Rodriguez, F., Tiwari, S., Sicilia, MA., Martín-Moncunill, D. (eds) Knowledge Graphs and Semantic Web . KGSWC 2022. Communications in Computer and Information Science, vol 1686. Springer, Cham. https://doi.org/10.1007/978-3-031-21422-6_18