Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling.
Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, 2025
Quantifying Privacy Risks of Public Statistics to Residents of Subsidized Housing.
CoRR, 2024
AI auditing: The Broken Bus on the Road to AI Accountability.
Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024
Learning to Live with Privacy-Preserving Analytics.
Commun. ACM, July, 2023
Upstream Mitigation Is Not All You Need: Testing the Bias Transfer Hypothesis in Pre-Trained Language Models.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
A set of distinct facial traits learned by machines is not predictive of appearance bias in the wild.
AI Ethics, 2021
Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021
Heuristic-Based Weak Learning for Moral Decision-Making.
CoRR, 2020
Machines Learn Appearance Bias in Face Recognition.
CoRR, 2020