19 citations · 31 across the 12 of their papers we have counts for
4 papers · 1 filter
Biased Programmers? Or Biased Data? A Field Experiment in Operationalizing AI Ethics
Bo Cowgill, Fabrizio Dell'Acqua, Samuel Deng +3
Why do biased predictions arise? What interventions can prevent them? We evaluate 8.2 million algorithmic predictions of math performance from 400 AI engineers, each of wh…
Is Private Learning Possible with Instance Encoding?
Nicholas Carlini, Samuel Deng, Sanjam Garg +6
A private machine learning algorithm hides as much as possible about its training data while still preserving accuracy. In this work, we study whether a non-private learning algori…
Ensuring Fairness Beyond the Training Data
Debmalya Mandal, Samuel Deng, Suman Jana +2
We initiate the study of fair classifiers that are robust to perturbations in the training distribution. Despite recent progress, the literature on fairness has largely ignored the…
A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks
Samuel Deng, Sanjam Garg, Somesh Jha +3
Poisoning attacks have emerged as a significant security threat to machine learning algorithms. It has been demonstrated that adversaries who make small changes to the training set…