Alexandra Chouldechova

According to our database, Alexandra Chouldechova authored at least 39 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Do Responsible AI Artifacts Advance Stakeholder Goals? Four Key Barriers Perceived by Legal and Civil Stakeholders.

Anna Kawakami, Daricia Wilkinson, Alexandra Chouldechova

CoRR, 2024

Algorithm-Assisted Decision Making and Racial Disparities in Housing: A Study of the Allegheny Housing Assessment Tool.

Lingwei Cheng, Cameron Drayton, Alexandra Chouldechova, Rhema Vaithianathan

CoRR, 2024

A structured regression approach for evaluating model performance across intersectional subgroups.

Christine Herlihy, Kimberly Truong, Alexandra Chouldechova, Miroslav Dudík

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

The Impact of Differential Feature Under-reporting on Algorithmic Fairness.

Nil-Jana Akpinar, Zachary C. Lipton, Alexandra Chouldechova

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023

Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints.

Jamelle Watson-Daniels, Solon Barocas, Jake M. Hofman, Alexandra Chouldechova

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Examining risks of racial biases in NLP tools for child protective services.

Anjalie Field, Amanda Coston, Nupoor Gandhi, Alexandra Chouldechova, Emily Putnam-Hornstein, David Steier, Yulia Tsvetkov

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Overcoming Algorithm Aversion: A Comparison between Process and Outcome Control.

Lingwei Cheng, Alexandra Chouldechova

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

2022

Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening.

Lingwei Cheng, Alexandra Chouldechova

Proc. ACM Hum. Comput. Interact., 2022

Doubting AI Predictions: Influence-Driven Second Opinion Recommendation.

Maria De-Arteaga, Alexandra Chouldechova, Artur Dubrawski

CoRR, 2022

Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders.

Logan Stapleton, Min Hun Lee, Diana Qing, Marya Wright, Alexandra Chouldechova, Ken Holstein, Zhiwei Steven Wu, Haiyi Zhu

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness.

Kate Donahue, Alexandra Chouldechova, Krishnaram Kenthapadi

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Algorithmic Fairness and Vertical Equity: Income Fairness with IRS Tax Audit Models.

Emily Black, Hadi Elzayn, Alexandra Chouldechova, Jacob Goldin, Daniel E. Ho

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Unsupervised and Semi-supervised Bias Benchmarking in Face Recognition.

Alexandra Chouldechova, Siqi Deng, Yongxin Wang, Wei Xia, Pietro Perona

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies.

Riccardo Fogliato, Alexandra Chouldechova, Zachary C. Lipton

Proc. ACM Hum. Comput. Interact., 2021

Leveraging Expert Consistency to Improve Algorithmic Decision Support.

Maria De-Arteaga, Artur Dubrawski, Alexandra Chouldechova

CoRR, 2021

Using a Machine Learning Tool to Support High-Stakes Decisions in Child Protection.

Rhema Vaithianathan, Diana Benavides Prado, Eric E. Dalton, Alexandra Chouldechova, Emily Putnam-Hornstein

AI Mag., 2021

Characterizing Fairness Over the Set of Good Models Under Selective Labels.

Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova

Proceedings of the 38th International Conference on Machine Learning, 2021

Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds.

Alan Mishler, Edward H. Kennedy, Alexandra Chouldechova

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy.

Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alexandra Chouldechova, Daniel E. Ho

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

The effect of differential victim crime reporting on predictive policing systems.

Nil-Jana Akpinar, Maria De-Arteaga, Alexandra Chouldechova

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systems.

Hao Fei Cheng, Logan Stapleton, Ruiqi Wang, Paige Bullock, Alexandra Chouldechova, Zhiwei Steven Wu, Haiyi Zhu

Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 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

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020

A snapshot of the frontiers of fairness in machine learning.

Alexandra Chouldechova, Aaron Roth

Commun. ACM, 2020

Counterfactual Predictions under Runtime Confounding.

Amanda Coston, Edward H. Kennedy, Alexandra Chouldechova

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Counterfactual risk assessments, evaluation, and fairness.

Amanda Coston, Alan Mishler, Edward H. Kennedy, Alexandra Chouldechova

Proceedings of the FAT* '20: Conference on Fairness, 2020

A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores.

Maria De-Arteaga, Riccardo Fogliato, Alexandra Chouldechova

Proceedings of the CHI '20: CHI Conference on Human Factors in Computing Systems, 2020

Fairness Evaluation in Presence of Biased Noisy Labels.

Riccardo Fogliato, Alexandra Chouldechova, Max G'Sell

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Counterfactual Risk Assessments, Evaluation, and Fairness.

Amanda Coston, Alexandra Chouldechova, Edward H. Kennedy

CoRR, 2019

What's in a Name? Reducing Bias in Bios without Access to Protected Attributes.

Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Kalai

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting.

Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai

Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

Toward Algorithmic Accountability in Public Services: A Qualitative Study of Affected Community Perspectives on Algorithmic Decision-making in Child Welfare Services.

Anna Brown, Alexandra Chouldechova, Emily Putnam-Hornstein, Andrew Tobin, Rhema Vaithianathan

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

2018

The Frontiers of Fairness in Machine Learning.

Alexandra Chouldechova, Aaron Roth

CoRR, 2018

Learning under selective labels in the presence of expert consistency.

Maria De-Arteaga, Artur Dubrawski, Alexandra Chouldechova

CoRR, 2018

Does mitigating ML's impact disparity require treatment disparity?

Zachary C. Lipton, Julian J. McAuley, Alexandra Chouldechova

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions.

Alexandra Chouldechova, Diana Benavides Prado, Oleksandr Fialko, Rhema Vaithianathan

Proceedings of the Conference on Fairness, Accountability and Transparency, 2018

2017

Does mitigating ML's disparate impact require disparate treatment?

Zachary C. Lipton, Alexandra Chouldechova, Julian J. McAuley

CoRR, 2017

Fairer and more accurate, but for whom?

Alexandra Chouldechova, Max G'Sell

CoRR, 2017

Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments.

Alexandra Chouldechova

Big Data, 2017

2013

Differences in search engine evaluations between query owners and non-owners.

Alexandra Chouldechova, David Mease

Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, 2013