Unfairness Detection
5 papers with code • 0 benchmarks • 2 datasets
Detection of unfairness in legal contracts' clauses.
Benchmarks
These leaderboards are used to track progress in Unfairness Detection
DemogPairs
Multilingual Terms of Service
Most implemented papers
CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service
Terms of service of on-line platforms too often contain clauses that are potentially unfair to the consumer.
Feature robustness and sex differences in medical imaging: a case study in MRI-based Alzheimer's disease detection
e-pet/adni-bias
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Instead, while logistic regression is fully robust to dataset composition, we find that CNN performance is generally improved for both male and female subjects when including more female subjects in the training dataset.
How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies
Recent studies have shown that robustness (the ability for a model to perform well on unseen data) plays a significant role in the type of strategy that should be used when approaching a new problem and, hence, measuring the robustness of these strategies has become a fundamental problem.
FairShap: A Data Re-weighting Approach for Algorithmic Fairness based on Shapley Values
Algorithmic fairness is of utmost societal importance, yet the current trend in large-scale machine learning models requires training with massive datasets that are frequently biased.
Signal Is Harder To Learn Than Bias: Debiasing with Focal Loss
mvandenhi/signal-is-harder
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We propose Signal is Harder (SiH), a variational-autoencoder-based method that simultaneously trains a biased and unbiased classifier using a novel, disentangling reweighting scheme inspired by the focal loss.
