Algorithmic Fairness
This invited paper reviews a framework to assist in mitigating societal risks that software can pose. This is to promote effective …
@inproceedings{baumTamingTheAIMonster2024,
author = {Kevin Baum and Biewer Sebastian and Hermanns Holger and Hetmank Sven and Langer Markus and Lauber-Rönsberg Anne and Sterz Sarah},
booktitle = {Model Checking Software - 30th International Symposium - Proceedings. International Symposium on Model Checking Software (SPIN-2024), April 8-9, Luxembourg City, Luxembourg},
doi = {10.1007/978-3-031-66149-5_1},
editor = {Thomas Neele and Anton Wijs},
month = {10},
pages = {3-25},
publisher = {Springer Nature, Switzerland},
series = {Lecture Notes in Computer Science, LNCS},
title = {Taming the AI Monster: Monitoring of Individual Fairness for Effective Human Oversight},
volume = {14624},
year = {2024}
}
This article introduces a framework that is meant to assist in mitigating societal risks that software can pose. Concretely, this …
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@article{biewerSoftwareDopingAnalysisFor2024,
author = {Sebastian Biewer and Kevin Baum and Sarah Sterz and Holger Hermanns and Sven Hetmank and Markus Langer and Anne Lauber-Rönsberg and Franz Lehr},
doi = {10.1007/s10703-024-00445-2},
journal = {Formal Methods in System Design},
month = {4},
pages = {1-50},
publisher = {Springer},
title = {Software doping analysis for human oversight},
url = {https://link.springer.com/article/10.1007/s10703-024-00445-2#Abs1},
volume = {62},
year = {2024}
}