Empirical audit of LAION-2B-en and LAION-2B-multi finds overrepresentation of young adults, White people, and males plus stereotypical emotion associations across two attribute classifiers.
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FASE pairs a spatiotemporal graph neural network and multivariate Hawkes process for crime prediction with a fairness-constrained linear program for patrol allocation, showing that allocation fairness holds in simulation but a 3.5 percentage point detection gap between minority and non-minority ZIPs
Proposes a quantitative transactional distributive fairness framework to enable systematic design of equitable decision-making systems in cybernetic societies.
citing papers explorer
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Unmasking LAION-5B: Age, Gender, Race, and Emotion Biases in Large-Scale Image Datasets
Empirical audit of LAION-2B-en and LAION-2B-multi finds overrepresentation of young adults, White people, and males plus stereotypical emotion associations across two attribute classifiers.
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FASE : A Fairness-Aware Spatiotemporal Event Graph Framework for Predictive Policing
FASE pairs a spatiotemporal graph neural network and multivariate Hawkes process for crime prediction with a fairness-constrained linear program for patrol allocation, showing that allocation fairness holds in simulation but a 3.5 percentage point detection gap between minority and non-minority ZIPs
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Quantitative Fairness -- A Framework For The Design Of Equitable Cybernetic Societies
Proposes a quantitative transactional distributive fairness framework to enable systematic design of equitable decision-making systems in cybernetic societies.