3 papers
cs.LG2025
The Benchmarking Epistemology: Construct Validity for Evaluating Machine Learning Models
Timo Freiesleben, Sebastian Zezulka
Predictive benchmarking, the evaluation of machine learning models based on predictive performance and competitive ranking, is a central epistemic practice in machine learning rese…
cs.CY2024
From the Fair Distribution of Predictions to the Fair Distribution of Social Goods: Evaluating the Impact of Fair Machine Learning on Long-Term Unemployment
Sebastian Zezulka, Konstantin Genin
Deploying an algorithmically informed policy is a significant intervention in society. Prominent methods for algorithmic fairness focus on the distribution of predictions at the ti…
cs.CY2023
Performativity and Prospective Fairness
Sebastian Zezulka, Konstantin Genin
Deploying an algorithmically informed policy is a significant intervention in the structure of society. As is increasingly acknowledged, predictive algorithms have performative eff…