On the Legal Compatibility of Fairness Definitions. - Alice Xiang; Inioluwa Deborah Raji (CoRR, 2019)

Explainable machine learning in deployment. - Umang Bhatt; Alice Xiang; Shubham Sharma 002; Adrian Weller; Ankur Taly; Yunhan Jia; Joydeep Ghosh; Ruchir Puri; José M. F. Moura; Peter Eckersley (FAT*, 2020)

Machine Learning Explainability for External Stakeholders. - Umang Bhatt; McKane Andrus; Adrian Weller; Alice Xiang (CoRR, 2020)

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. - Umang Bhatt; Yunfeng Zhang; Javier Antorán; Q. Vera Liao; Prasanna Sattigeri; Riccardo Fogliato; Gabrielle Gauthier Melançon; Ranganath Krishnan; Jason Stanley; Omesh Tickoo; Lama Nachman; Rumi Chunara; et al. (CoRR, 2020)

Affirmative Algorithms: The Legal Grounds for Fairness as Awareness. - Daniel E. Ho; Alice Xiang (CoRR, 2020)

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. - Umang Bhatt; Javier Antorán; Yunfeng Zhang; Q. Vera Liao; Prasanna Sattigeri; Riccardo Fogliato; Gabrielle Gauthier Melançon; Ranganath Krishnan; Jason Stanley; Omesh Tickoo; Lama Nachman; Rumi Chunara; et al. (AIES, 2021)

On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes. - Riccardo Fogliato; Alice Xiang; Zachary C. Lipton; Daniel Nagin; Alexandra Chouldechova (AIES, 2021)

What We Can't Measure, We Can't Understand: Challenges to Demographic Data Procurement in the Pursuit of Fairness. - McKane Andrus; Elena Spitzer; Jeffrey Brown; Alice Xiang (FAccT, 2021)

A Multistakeholder Approach Towards Evaluating AI Transparency Mechanisms. - Ana Lucic; Madhulika Srikumar; Umang Bhatt; Alice Xiang; Ankur Taly; Q. Vera Liao; Maarten de Rijke (CoRR, 2021)

Attrition of Workers with Minoritized Identities on AI Teams. - Jeffrey Brown; Tina M. Park; Jiyoo Chang; McKane Andrus; Alice Xiang; Christine Custis (EAAMO, 2022)

Regulating Facial Processing Technologies: Tensions Between Legal and Technical Considerations in the Application of Illinois BIPA. - Rui-Jie Yew; Alice Xiang (FAccT, 2022)

Promises and Challenges of Causality for Ethical Machine Learning. - Aida Rahmattalabi; Alice Xiang (CoRR, 2022)

Towards the Use of Saliency Maps for Explaining Low-Quality Electrocardiograms to End Users. - Ana Lucic; Sheeraz Ahmad; Amanda Furtado Brinhosa; Vera Liao; Himani Agrawal; Umang Bhatt; Krishnaram Kenthapadi; Alice Xiang; Maarten de Rijke; Nicholas Drabowski (CoRR, 2022)

Flickr Africa: Examining Geo-Diversity in Large-Scale, Human-Centric Visual Data. - Keziah Naggita; Julienne LaChance; Alice Xiang (AIES, 2023)

Augmented Datasheets for Speech Datasets and Ethical Decision-Making. - Orestis Papakyriakopoulos; Anna Seo Gyeong Choi; William Thong; Dora Zhao; Jerone Theodore Alexander Andrews; Rebecca Bourke; Alice Xiang; Allison Koenecke (FAccT, 2023)

Beyond Skin Tone: A Multidimensional Measure of Apparent Skin Color. - William Thong; Przemyslaw Joniak; Alice Xiang (ICCV, 2023)

A View From Somewhere: Human-Centric Face Representations. - Jerone Theodore Alexander Andrews; Przemyslaw Joniak; Alice Xiang (ICLR, 2023)

Men Also Do Laundry: Multi-Attribute Bias Amplification. - Dora Zhao; Jerone Theodore Alexander Andrews; Alice Xiang (ICML, 2023)

Ethical Considerations for Responsible Data Curation. - Jerone Theodore Alexander Andrews; Dora Zhao; William Thong; Apostolos Modas; Orestis Papakyriakopoulos; Alice Xiang (NeurIPS, 2023)

Considerations for Ethical Speech Recognition Datasets. - Orestis Papakyriakopoulos; Alice Xiang (WSDM, 2023)

Ethical Considerations for Collecting Human-Centric Image Datasets. - Jerone T. A. Andrews; Dora Zhao; William Thong; Apostolos Modas; Orestis Papakyriakopoulos; Shruti Nagpal; Alice Xiang (CoRR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Efficient Bias Mitigation Without Privileged Information. - Mateo Espinosa Zarlenga; Swami Sankaranarayanan; Jerone T. A. Andrews; Zohreh Shams; Mateja Jamnik; Alice Xiang (ECCV (72), 2024)

Resampled Datasets Are Not Enough: Mitigating Societal Bias Beyond Single Attributes. - Yusuke Hirota; Jerone Theodore Alexander Andrews; Dora Zhao; Orestis Papakyriakopoulos; Apostolos Modas; Yuta Nakashima; Alice Xiang (EMNLP, 2024)

Not My Voice! A Taxonomy of Ethical and Safety Harms of Speech Generators. - Wiebke Hutiri; Orestis Papakyriakopoulos; Alice Xiang (FAccT, 2024)

Position: Measure Dataset Diversity, Don't Just Claim It. - Dora Zhao; Jerone T. A. Andrews; Orestis Papakyriakopoulos; Alice Xiang (ICML, 2024)

A Taxonomy of Challenges to Curating Fair Datasets. - Dora Zhao; Morgan Klaus Scheuerman; Pooja Chitre; Jerone Theodore Alexander Andrews; Georgia Panagiotidou; Shawn Walker; Kathleen H. Pine; Alice Xiang (NeurIPS, 2024)

GenDataAgent: On-the-fly Dataset Augmentation with Synthetic Data. - Zhiteng Li; Lele Chen; Jerone T. A. Andrews; Yunhao Ba; Yulun Zhang 001; Alice Xiang (ICLR, 2025)

TEDI: Trustworthy and Ethical Dataset Indicators to Analyze and Compare Dataset Documentation. - Wiebke Hutiri; Mircea Cimpoi; Morgan Klaus Scheuerman; Victoria Matthews; Alice Xiang (CoRR, 2025)