Soumyajit Gupta, Sooyong Lee, Maria De-Arteaga, and Matthew Lease. 2023. Same, But Different: Conditional Multi-Task Learning for Demographic-Specific Toxicity Detection. Proceedings of the ACM Web Conference, WWW 2023.

Kenneth Holstein, Maria De-Arteaga, Lakshmi Tumati, and Yanghuidi Cheng. April 2023. Toward Supporting Perceptual Complementarity in Human-AI Collaboration via Reflection on Unobservables.  Proceedings of the ACM on Human-Computer Interaction 7(CSCW1):1-20.

Jonathan Elmer, Michael Kurz, Patrick Coppler, Alexis Steinberg, Stephanie DeMasi, Maria De-Arteaga, Noah Simon, Vladimir Zadorozhny, Katharyn Flickinger, and Clifton Callaway Time to Awakening and Self-Fulfilling Prophecies After Cardiac Arrest. Critical Care Medicine.  Forthcoming.

Myra Cheng, Maria De-Arteaga, Lester Mackey, and Adam T. Kalai. Social Norm Bias: Residual Harms of Fairness-Aware Algorithms. Data Mining and Knowledge Discovery. Forthcoming.

Yunyi Li, Maria De-Arteaga, and Maytal Saar-Tsechansky. When More Data Lead Us Astray: Active Data Acquisition in the Presence of Label Bias. Proceedings of the Tenth AAAI Conference on Human Computation and Crowdsourcing 10(1):133-146.

Maria De-Arteaga and Jonathan Elmer. Self-fulfilling Prophecies and Machine Learning in Resuscitation Science. Resuscitation.  Forthcoming.

Maria De‐Arteaga, Stefan Feuerriegel, and Maytal Saar‐Tsechansky. Oct 2022. Algorithmic Fairness in Business Analytics: Directions for Research and Practice. Production & Operations Management 31(10): 3749-3770.

Maria De-Arteaga, Sina Fazelpour. Diversity in Sociotechnical Machine Learning Systems. Big Data & Society. Forthcoming.

Vincent Jeanselme, Maria De Arteaga Gonzalez, Jonathan Elmer, Sarah M. Perman, and Artur Dubrawski. Gender Differences in Post Cardiac Arrest Discharge Locations. Resuscitation Plus, forthcoming.