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cs.LG2025
Bias Begins with Data: The FairGround Corpus for Robust and Reproducible Research on Algorithmic Fairness
Jan Simson, Alessandro Fabris, Cosima Fröhner +2
As machine learning (ML) systems are increasingly adopted in high-stakes decision-making domains, ensuring fairness in their outputs has become a central challenge. At the core of…
cs.LG2024★ 11 cited
Lazy Data Practices Harm Fairness Research
Jan Simson, Alessandro Fabris, Christoph Kern
Data practices shape research and practice on fairness in machine learning (fair ML). Critical data studies offer important reflections and critiques for the responsible advancemen…