Individual Fairness Through Reweighting and Tuning

arXiv:2405.01711v1 Announce Type: new
Abstract: Inherent bias within society can be amplified and perpetuated by artificial intelligence (AI) systems. To address this issue, a wide range of solutions have been proposed to identify and mitigate bias and enforce fairness for individuals and groups. Recently, Graph Laplacian Regularizer (GLR), a regularization technique from the semi-supervised learning literature has been used as a substitute for the common Lipschitz condition to enhance individual fairness (IF). Notable prior work has shown that enforcing IF …

abstract artificial artificial intelligence arxiv bias cs.ai cs.lg fairness graph identify intelligence issue regularization semi-supervised society solutions systems through type