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Found 3 papers, 1 papers with code
Backpropagation Clipping for Deep Learning with Differential Privacy
We present backpropagation clipping, a novel variant of differentially private stochastic gradient descent (DP-SGD) for privacy-preserving deep learning.
Prediction Sensitivity: Continual Audit of Counterfactual Fairness in Deployed Classifiers
As AI-based systems increasingly impact many areas of our lives, auditing these systems for fairness is an increasingly high-stakes problem.
Towards Auditability for Fairness in Deep Learning
Group fairness metrics can detect when a deep learning model behaves differently for advantaged and disadvantaged groups, but even models that score well on these metrics can make blatantly unfair predictions.
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