12 citations · 23 across the 4 of their papers we have counts for
4 papers
Evaluating Intellectual Property Guardrails of Generative Image Models: A Technical Report
Austin T. Hoag, Apostolos Modas, Yunhao Ba +9
Generative image models are capable of producing images that bear a strong resemblance to, or replicate, recognizable intellectual property (IP). In this technical report, we prese…
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…
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…
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
A vast number of systems across the world use algorithmic decision making (ADM) to (partially) automate decisions that have previously been made by humans. The downstream effects o…