Alex Chouldechova

Senior Principal Researcher

Publications

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- Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems
  
  Emma Harvey, Emily Sheng, Su Lin Blodgett, Alex Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna Wallach
  
  Findings of the Association for Computational Linguistics: ACL 2025 | July 2025
  
  Publication
- Taxonomizing Representational Harms using Speech Act Theory
  
  Emily Corvi, Hannah Washington, Stefanie Reed, Chad Atalla, Alex Chouldechova, Alex Dow, Jean Garcia-Gathright, Nick Pangakis, Emily Sheng, Dan Vann, Matthew Vogel, Hanna Wallach
  
  March 2025
  
  Publication
- Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alex Chouldechova, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nick Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  ICML 2025 | January 2025
  
  Publication
- A Shared Standard for Valid Measurement of Generative AI Systems’ Capabilities, Risks, and Impacts
  
  Alex Chouldechova, Chad Atalla, Solon Barocas, A. Feder Cooper, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Nick Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Matthew Vogel, Hannah Washington, Hanna Wallach
  
  December 2024
  
  Publication
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Published by Microsoft
  
  Publication Project Project
- Gaps Between Research and Practice When Measuring Representational Harms Caused by LLM-Based Systems
  
  Emma Harvey, Emily Sheng, Su Lin Blodgett, Alex Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna Wallach
  
  November 2024
  
  Publication
- Dimensions of Generative AI Evaluation Design
  
  Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alex Chouldechova, Hanna Wallach
  
  November 2024
  
  Publication
- Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, Nick Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alex Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  November 2024
  
  Publication
- SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation
  
  Lester Mackey, Miro Dudík, Alex Chouldechova
  
  October 2024
- A structured regression approach for evaluating model performance across intersectional subgroups
  
  Christine Herlihy, Kimberly Truong, Alex Chouldechova, Miro Dudík
  
  FAccT 2024 | January 2024
  
  DOI Publication Publication
- Unsupervised and semi-supervised bias benchmarking in face recognition
  
  Alex Chouldechova, Siqi Deng, Yongxin Wang, Wei Xia, Pietro Perona
  
  Computer Vision–ECCV 2022 | November 2022
  
  PDF
- Algorithmic fairness and vertical equity: Income fairness with IRS tax audit models
  
  Emily Black, Hadi Elzayn, Alex Chouldechova, Jacob Goldin, Daniel Ho
  
  2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
  
  Publication
- Human-algorithm collaboration: Achieving complementarity and avoiding unfairness
  
  Kate Donahue, Alex Chouldechova, Krishnaram Kenthapadi
  
  2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
  
  PDF
- Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders
  
  Logan Stapleton, Min Hun Lee, Diana Qing, Marya Wright, Alex Chouldechova, Ken Holstein, Zhiwei Steven Wu, Haiyi Zhu
  
  2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
  
  PDF
- Doubting AI Predictions: Influence-Driven Second Opinion Recommendation
  
  Maria De-Arteaga, Alex Chouldechova, Artur Dubrawski
  
  April 2022
  
  PDF
- Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening
  
  Lingwei Cheng, Alex Chouldechova
  
  April 2022
  
  PDF
- The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies
  
  Riccardo Fogliato, Alex Chouldechova, Zachary Lipton
  
  ACM on Human-Computer Interaction | September 2021
  
  Publication
- Quality of life and functional status of patients treated with venovenous extracorporeal membrane oxygenation at 6 months
  
  Hussein D. Kanji, Alex Chouldechova, Samantha Harris-Fox, Juan J. Ronco, Ephraim O'dea, Chris Harvey, Constantin Shuster, Sonny Thiara, Giles J. Peek
  
  Journal of Critical Care | August 2021, Vol 66: pp. 26-30
  
  DOI Publication
- Characterizing Fairness Over the Set of Good Models Under Selective Labels
  
  Amanda Coston, Ashesh Rambachan, Alex Chouldechova
  
  2021 International Conference on Machine Learning | July 2021
  
  PDF Publication
- On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes
  
  Riccardo Fogliato, Alice Xiang, Zachary Lipton, Daniel Nagin, Alex Chouldechova
  
  2021 AAAI/ACM Conference on AI, Ethics, and Society | May 2021
  
  Publication
- The effect of differential victim crime reporting on predictive policing systems
  
  Nil-Jana Akpinar, Maria De-Arteaga, Alex Chouldechova
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | March 2021
  
  DOI PDF
- Soliciting Stakeholders’ Fairness Notions in Child Maltreatment Predictive Systems
  
  Hao-Fei Cheng, Logan Stapleton, Ruiqi Wang, Paige Bullock, Alex Chouldechova, Zhiwei Steven Wu, Haiyi Zhu
  
  2021 Human Factors in Computing Systems | January 2021
  
  DOI Publication
- Leveraging Expert Consistency to Improve Algorithmic Decision Support
  
  Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
  
  January 2021
  
  Publication
- Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy
  
  Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alex Chouldechova, Daniel E. Ho
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | November 2020
  
  DOI Publication
- Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds
  
  Alan Mishler, Edward H. Kennedy, Alex Chouldechova
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | September 2020
  
  DOI Publication
- Hospital Injury Encounters of Children Identified by a Predictive Risk Model for Screening Child Maltreatment Referrals: Evidence From the Allegheny Family Screening Tool
  
  Rhema Vaithianathan, Emily Putnam-Hornstein, Alex Chouldechova, Diana Benavides-Prado, Rachel Berger
  
  JAMA Pediatrics | August 2020, Vol 174(11): pp. 1-6
  
  DOI Publication
- The Present and Future of AI in Pre-Trial Risk Assessment Instruments
  
  Alex Chouldechova, Kristian Lum
  
  June 2020
  
  PDF
- A group of industry, academic, and government experts convene in Philadelphia to explore the roots of algorithmic bias
  
  Alex Chouldechova, Aaron Roth
  
  Communications of the ACM | May 2020, Vol 63(5): pp. 82-89
  
  Publication
- Counterfactual predictions under runtime confounding
  
  Amanda Coston, Edward H. Kennedy, Alex Chouldechova
  
  2020 Neural Information Processing Systems | May 2020
  
  PDF
- A snapshot of the frontiers of fairness in machine learning
  
  Alex Chouldechova, Aaron Roth
  
  Communications of The ACM | April 2020, Vol 63(5): pp. 82-89
  
  DOI Publication
- Transparency and Simplicity in Criminal Risk Assessment
  
  Alex Chouldechova
  
  Harvard Data Science Review | March 2020, Vol 2(1)
  
  DOI Publication
- Fairness Evaluation in Presence of Biased Noisy Labels
  
  Riccardo Fogliato, Max Grazier G'Sell, Alex Chouldechova
  
  International Conference on Artificial Intelligence and Statistics | March 2020
  
  Publication
- A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores
  
  Maria De-Arteaga, Riccardo Fogliato, Alex Chouldechova
  
  2020 Human Factors in Computing Systems | February 2020
  
  DOI Publication
- Toward Algorithmic Accountability in Public Services: A Qualitative Study of Affected Community Perspectives on Algorithmic Decision-making in Child Welfare Services
  
  Anna Brown, Alex Chouldechova, Emily Putnam-Hornstein, Andrew Tobin, Rhema Vaithianathan
  
  2019 Human Factors in Computing Systems | May 2019
  
  DOI PDF
- What’s in a Name? Reducing Bias in Bios without Access to Protected Attributes
  
  Alexey Romanov, Maria De-Arteaga, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alex Chouldechova, Sahin Geyik, krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai
  
  NAACL 2019 | April 2019
  
  Best Paper Award, NAACL 2019
  
  Publication
- Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting
  
  Maria De-Arteaga, Alexey Romanov, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alex Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
  
  FAT* ’19: Conference on Fairness, Accountability, and Transparency | January 2019
  
  PDF DOI Github
- The Frontiers of Fairness in Machine Learning
  
  Alex Chouldechova, Aaron Roth
  
  October 2018
  
  Publication
- Learning under selective labels in the presence of expert consistency
  
  Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
  
  July 2018
  
  Publication
- Does mitigating ML’s impact disparity require treatment disparity?
  
  Zachary Lipton, Julian McAuley, Alex Chouldechova
  
  2018 Neural Information Processing Systems | March 2018
  
  Publication
- Teach {IT}: Turning the Classroom into a Research Laboratory via Interactive E-Learning Tools
  
  Philipp Burckhardt, Alex Chouldechova, Rebecca Nugent
  
  International Conference on Teaching Statistics | March 2018
  
  PDF
- A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions
  
  Alex Chouldechova, Diana Benavides-Prado, Oleksandr Fialko, Rhema Vaithianathan
  
  Conference on Fairness, Accountability and Transparency | January 2018
  
  PDF
- Fairer and more accurate, but for whom?
  
  Alex Chouldechova, Max Grazier G'Sell
  
  June 2017
  
  Publication
- Safety and Outcomes of Mobile ECMO Using a Bicaval Dual-Stage Venous Catheter
  
  Hussein D. Kanji, Alex Chouldechova, Chris Harvey, Ephraim O'dea, Gail Faulkner, Giles J. Peek
  
  Asaio Journal | April 2017, Vol 63(3): pp. 351-355
  
  DOI Publication
- Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
  
  Alex Chouldechova
  
  Big Data | October 2016, Vol 5(2): pp. 153-163
  
  Publication
- Sequential selection procedures and false discovery rate control
  
  Max Grazier G'Sell, Stefan Wager, Alex Chouldechova, Robert Tibshirani
  
  Journal of The Royal Statistical Society Series B-statistical Methodology | February 2016, Vol 78(2): pp. 423-444
  
  DOI
- Generalized Additive Model Selection
  
  Alex Chouldechova, Trevor Hastie
  
  June 2015
  
  Publication

- Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems
  
  Emma Harvey, Emily Sheng, Su Lin Blodgett, Alex Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna Wallach
  
  Findings of the Association for Computational Linguistics: ACL 2025 | July 2025
  
  Publication
- What’s in a Name? Reducing Bias in Bios without Access to Protected Attributes
  
  Alexey Romanov, Maria De-Arteaga, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alex Chouldechova, Sahin Geyik, krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai
  
  NAACL 2019 | April 2019
  
  Best Paper Award, NAACL 2019
  
  Publication
- Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems
  
  Emma Harvey, Emily Sheng, Su Lin Blodgett, Alex Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna Wallach
  
  Findings of the Association for Computational Linguistics: ACL 2025 | July 2025
  
  Publication
- Taxonomizing Representational Harms using Speech Act Theory
  
  Emily Corvi, Hannah Washington, Stefanie Reed, Chad Atalla, Alex Chouldechova, Alex Dow, Jean Garcia-Gathright, Nick Pangakis, Emily Sheng, Dan Vann, Matthew Vogel, Hanna Wallach
  
  March 2025
  
  Publication
- Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alex Chouldechova, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nick Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  ICML 2025 | January 2025
  
  Publication
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Published by Microsoft
  
  Publication Project Project
- A Shared Standard for Valid Measurement of Generative AI Systems’ Capabilities, Risks, and Impacts
  
  Alex Chouldechova, Chad Atalla, Solon Barocas, A. Feder Cooper, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Nick Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Matthew Vogel, Hannah Washington, Hanna Wallach
  
  December 2024
  
  Publication
- Gaps Between Research and Practice When Measuring Representational Harms Caused by LLM-Based Systems
  
  Emma Harvey, Emily Sheng, Su Lin Blodgett, Alex Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna Wallach
  
  November 2024
  
  Publication
- Dimensions of Generative AI Evaluation Design
  
  Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alex Chouldechova, Hanna Wallach
  
  November 2024
  
  Publication
- Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, Nick Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alex Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  November 2024
  
  Publication
- A structured regression approach for evaluating model performance across intersectional subgroups
  
  Christine Herlihy, Kimberly Truong, Alex Chouldechova, Miro Dudík
  
  FAccT 2024 | January 2024
  
  DOI Publication Publication
- Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders
  
  Logan Stapleton, Min Hun Lee, Diana Qing, Marya Wright, Alex Chouldechova, Ken Holstein, Zhiwei Steven Wu, Haiyi Zhu
  
  2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
  
  PDF
- Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening
  
  Lingwei Cheng, Alex Chouldechova
  
  April 2022
  
  PDF
- On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes
  
  Riccardo Fogliato, Alice Xiang, Zachary Lipton, Daniel Nagin, Alex Chouldechova
  
  2021 AAAI/ACM Conference on AI, Ethics, and Society | May 2021
  
  Publication
- The effect of differential victim crime reporting on predictive policing systems
  
  Nil-Jana Akpinar, Maria De-Arteaga, Alex Chouldechova
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | March 2021
  
  DOI PDF
- Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy
  
  Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alex Chouldechova, Daniel E. Ho
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | November 2020
  
  DOI Publication
- Hospital Injury Encounters of Children Identified by a Predictive Risk Model for Screening Child Maltreatment Referrals: Evidence From the Allegheny Family Screening Tool
  
  Rhema Vaithianathan, Emily Putnam-Hornstein, Alex Chouldechova, Diana Benavides-Prado, Rachel Berger
  
  JAMA Pediatrics | August 2020, Vol 174(11): pp. 1-6
  
  DOI Publication
- Fairness Evaluation in Presence of Biased Noisy Labels
  
  Riccardo Fogliato, Max Grazier G'Sell, Alex Chouldechova
  
  International Conference on Artificial Intelligence and Statistics | March 2020
  
  Publication
- Toward Algorithmic Accountability in Public Services: A Qualitative Study of Affected Community Perspectives on Algorithmic Decision-making in Child Welfare Services
  
  Anna Brown, Alex Chouldechova, Emily Putnam-Hornstein, Andrew Tobin, Rhema Vaithianathan
  
  2019 Human Factors in Computing Systems | May 2019
  
  DOI PDF
- What’s in a Name? Reducing Bias in Bios without Access to Protected Attributes
  
  Alexey Romanov, Maria De-Arteaga, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alex Chouldechova, Sahin Geyik, krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai
  
  NAACL 2019 | April 2019
  
  Best Paper Award, NAACL 2019
  
  Publication
- Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting
  
  Maria De-Arteaga, Alexey Romanov, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alex Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
  
  FAT* ’19: Conference on Fairness, Accountability, and Transparency | January 2019
  
  PDF DOI Github
- A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions
  
  Alex Chouldechova, Diana Benavides-Prado, Oleksandr Fialko, Rhema Vaithianathan
  
  Conference on Fairness, Accountability and Transparency | January 2018
  
  PDF
- Fairer and more accurate, but for whom?
  
  Alex Chouldechova, Max Grazier G'Sell
  
  June 2017
  
  Publication
- Taxonomizing Representational Harms using Speech Act Theory
  
  Emily Corvi, Hannah Washington, Stefanie Reed, Chad Atalla, Alex Chouldechova, Alex Dow, Jean Garcia-Gathright, Nick Pangakis, Emily Sheng, Dan Vann, Matthew Vogel, Hanna Wallach
  
  March 2025
  
  Publication
- Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alex Chouldechova, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nick Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  ICML 2025 | January 2025
  
  Publication
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Published by Microsoft
  
  Publication Project Project
- A Shared Standard for Valid Measurement of Generative AI Systems’ Capabilities, Risks, and Impacts
  
  Alex Chouldechova, Chad Atalla, Solon Barocas, A. Feder Cooper, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Nick Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Matthew Vogel, Hannah Washington, Hanna Wallach
  
  December 2024
  
  Publication
- Gaps Between Research and Practice When Measuring Representational Harms Caused by LLM-Based Systems
  
  Emma Harvey, Emily Sheng, Su Lin Blodgett, Alex Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna Wallach
  
  November 2024
  
  Publication
- Dimensions of Generative AI Evaluation Design
  
  Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alex Chouldechova, Hanna Wallach
  
  November 2024
  
  Publication
- Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, Nick Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alex Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  November 2024
  
  Publication
- SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation
  
  Lester Mackey, Miro Dudík, Alex Chouldechova
  
  October 2024
- Unsupervised and semi-supervised bias benchmarking in face recognition
  
  Alex Chouldechova, Siqi Deng, Yongxin Wang, Wei Xia, Pietro Perona
  
  Computer Vision–ECCV 2022 | November 2022
  
  PDF
- Algorithmic fairness and vertical equity: Income fairness with IRS tax audit models
  
  Emily Black, Hadi Elzayn, Alex Chouldechova, Jacob Goldin, Daniel Ho
  
  2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
  
  Publication
- Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders
  
  Logan Stapleton, Min Hun Lee, Diana Qing, Marya Wright, Alex Chouldechova, Ken Holstein, Zhiwei Steven Wu, Haiyi Zhu
  
  2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
  
  PDF
- Human-algorithm collaboration: Achieving complementarity and avoiding unfairness
  
  Kate Donahue, Alex Chouldechova, Krishnaram Kenthapadi
  
  2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
  
  PDF
- Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening
  
  Lingwei Cheng, Alex Chouldechova
  
  April 2022
  
  PDF
- Characterizing Fairness Over the Set of Good Models Under Selective Labels
  
  Amanda Coston, Ashesh Rambachan, Alex Chouldechova
  
  2021 International Conference on Machine Learning | July 2021
  
  PDF Publication
- The effect of differential victim crime reporting on predictive policing systems
  
  Nil-Jana Akpinar, Maria De-Arteaga, Alex Chouldechova
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | March 2021
  
  DOI PDF
- Soliciting Stakeholders’ Fairness Notions in Child Maltreatment Predictive Systems
  
  Hao-Fei Cheng, Logan Stapleton, Ruiqi Wang, Paige Bullock, Alex Chouldechova, Zhiwei Steven Wu, Haiyi Zhu
  
  2021 Human Factors in Computing Systems | January 2021
  
  DOI Publication
- Leveraging Expert Consistency to Improve Algorithmic Decision Support
  
  Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
  
  January 2021
  
  Publication
- Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy
  
  Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alex Chouldechova, Daniel E. Ho
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | November 2020
  
  DOI Publication
- Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds
  
  Alan Mishler, Edward H. Kennedy, Alex Chouldechova
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | September 2020
  
  DOI Publication
- The Present and Future of AI in Pre-Trial Risk Assessment Instruments
  
  Alex Chouldechova, Kristian Lum
  
  June 2020
  
  PDF
- Counterfactual predictions under runtime confounding
  
  Amanda Coston, Edward H. Kennedy, Alex Chouldechova
  
  2020 Neural Information Processing Systems | May 2020
  
  PDF
- A group of industry, academic, and government experts convene in Philadelphia to explore the roots of algorithmic bias
  
  Alex Chouldechova, Aaron Roth
  
  Communications of the ACM | May 2020, Vol 63(5): pp. 82-89
  
  Publication
- A snapshot of the frontiers of fairness in machine learning
  
  Alex Chouldechova, Aaron Roth
  
  Communications of The ACM | April 2020, Vol 63(5): pp. 82-89
  
  DOI Publication
- Transparency and Simplicity in Criminal Risk Assessment
  
  Alex Chouldechova
  
  Harvard Data Science Review | March 2020, Vol 2(1)
  
  DOI Publication
- Fairness Evaluation in Presence of Biased Noisy Labels
  
  Riccardo Fogliato, Max Grazier G'Sell, Alex Chouldechova
  
  International Conference on Artificial Intelligence and Statistics | March 2020
  
  Publication
- A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores
  
  Maria De-Arteaga, Riccardo Fogliato, Alex Chouldechova
  
  2020 Human Factors in Computing Systems | February 2020
  
  DOI Publication
- Toward Algorithmic Accountability in Public Services: A Qualitative Study of Affected Community Perspectives on Algorithmic Decision-making in Child Welfare Services
  
  Anna Brown, Alex Chouldechova, Emily Putnam-Hornstein, Andrew Tobin, Rhema Vaithianathan
  
  2019 Human Factors in Computing Systems | May 2019
  
  DOI PDF
- What’s in a Name? Reducing Bias in Bios without Access to Protected Attributes
  
  Alexey Romanov, Maria De-Arteaga, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alex Chouldechova, Sahin Geyik, krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai
  
  NAACL 2019 | April 2019
  
  Best Paper Award, NAACL 2019
  
  Publication
- The Frontiers of Fairness in Machine Learning
  
  Alex Chouldechova, Aaron Roth
  
  October 2018
  
  Publication
- Learning under selective labels in the presence of expert consistency
  
  Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
  
  July 2018
  
  Publication
- Teach {IT}: Turning the Classroom into a Research Laboratory via Interactive E-Learning Tools
  
  Philipp Burckhardt, Alex Chouldechova, Rebecca Nugent
  
  International Conference on Teaching Statistics | March 2018
  
  PDF
- Does mitigating ML’s impact disparity require treatment disparity?
  
  Zachary Lipton, Julian McAuley, Alex Chouldechova
  
  2018 Neural Information Processing Systems | March 2018
  
  Publication
- A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions
  
  Alex Chouldechova, Diana Benavides-Prado, Oleksandr Fialko, Rhema Vaithianathan
  
  Conference on Fairness, Accountability and Transparency | January 2018
  
  PDF
- Fairer and more accurate, but for whom?
  
  Alex Chouldechova, Max Grazier G'Sell
  
  June 2017
  
  Publication
- Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
  
  Alex Chouldechova
  
  Big Data | October 2016, Vol 5(2): pp. 153-163
  
  Publication
- Sequential selection procedures and false discovery rate control
  
  Max Grazier G'Sell, Stefan Wager, Alex Chouldechova, Robert Tibshirani
  
  Journal of The Royal Statistical Society Series B-statistical Methodology | February 2016, Vol 78(2): pp. 423-444
  
  DOI
- Generalized Additive Model Selection
  
  Alex Chouldechova, Trevor Hastie
  
  June 2015
  
  Publication
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Published by Microsoft
  
  Publication Project Project
- Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy
  
  Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alex Chouldechova, Daniel E. Ho
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | November 2020
  
  DOI Publication
- Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
  
  Alex Chouldechova
  
  Big Data | October 2016, Vol 5(2): pp. 153-163
  
  Publication
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Published by Microsoft
  
  Publication Project Project
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Published by Microsoft
  
  Publication Project Project
- Human-algorithm collaboration: Achieving complementarity and avoiding unfairness
  
  Kate Donahue, Alex Chouldechova, Krishnaram Kenthapadi
  
  2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
  
  PDF
- Doubting AI Predictions: Influence-Driven Second Opinion Recommendation
  
  Maria De-Arteaga, Alex Chouldechova, Artur Dubrawski
  
  April 2022
  
  PDF
- The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies
  
  Riccardo Fogliato, Alex Chouldechova, Zachary Lipton
  
  ACM on Human-Computer Interaction | September 2021
  
  Publication
- Characterizing Fairness Over the Set of Good Models Under Selective Labels
  
  Amanda Coston, Ashesh Rambachan, Alex Chouldechova
  
  2021 International Conference on Machine Learning | July 2021
  
  PDF Publication
- On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes
  
  Riccardo Fogliato, Alice Xiang, Zachary Lipton, Daniel Nagin, Alex Chouldechova
  
  2021 AAAI/ACM Conference on AI, Ethics, and Society | May 2021
  
  Publication
- The effect of differential victim crime reporting on predictive policing systems
  
  Nil-Jana Akpinar, Maria De-Arteaga, Alex Chouldechova
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | March 2021
  
  DOI PDF
- Soliciting Stakeholders’ Fairness Notions in Child Maltreatment Predictive Systems
  
  Hao-Fei Cheng, Logan Stapleton, Ruiqi Wang, Paige Bullock, Alex Chouldechova, Zhiwei Steven Wu, Haiyi Zhu
  
  2021 Human Factors in Computing Systems | January 2021
  
  DOI Publication
- Leveraging Expert Consistency to Improve Algorithmic Decision Support
  
  Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
  
  January 2021
  
  Publication
- Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds
  
  Alan Mishler, Edward H. Kennedy, Alex Chouldechova
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | September 2020
  
  DOI Publication
- A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores
  
  Maria De-Arteaga, Riccardo Fogliato, Alex Chouldechova
  
  2020 Human Factors in Computing Systems | February 2020
  
  DOI Publication
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Published by Microsoft
  
  Publication Project Project
- Quality of life and functional status of patients treated with venovenous extracorporeal membrane oxygenation at 6 months
  
  Hussein D. Kanji, Alex Chouldechova, Samantha Harris-Fox, Juan J. Ronco, Ephraim O'dea, Chris Harvey, Constantin Shuster, Sonny Thiara, Giles J. Peek
  
  Journal of Critical Care | August 2021, Vol 66: pp. 26-30
  
  DOI Publication
- Hospital Injury Encounters of Children Identified by a Predictive Risk Model for Screening Child Maltreatment Referrals: Evidence From the Allegheny Family Screening Tool
  
  Rhema Vaithianathan, Emily Putnam-Hornstein, Alex Chouldechova, Diana Benavides-Prado, Rachel Berger
  
  JAMA Pediatrics | August 2020, Vol 174(11): pp. 1-6
  
  DOI Publication
- Safety and Outcomes of Mobile ECMO Using a Bicaval Dual-Stage Venous Catheter
  
  Hussein D. Kanji, Alex Chouldechova, Chris Harvey, Ephraim O'dea, Gail Faulkner, Giles J. Peek
  
  Asaio Journal | April 2017, Vol 63(3): pp. 351-355
  
  DOI Publication
- The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies
  
  Riccardo Fogliato, Alex Chouldechova, Zachary Lipton
  
  ACM on Human-Computer Interaction | September 2021
  
  Publication
- A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores
  
  Maria De-Arteaga, Riccardo Fogliato, Alex Chouldechova
  
  2020 Human Factors in Computing Systems | February 2020
  
  DOI Publication

- Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems
  
  Emma Harvey, Emily Sheng, Su Lin Blodgett, Alex Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna Wallach
  
  Findings of the Association for Computational Linguistics: ACL 2025 | July 2025
  
  Publication
- Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alex Chouldechova, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nick Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  ICML 2025 | January 2025
  
  Publication
- A structured regression approach for evaluating model performance across intersectional subgroups
  
  Christine Herlihy, Kimberly Truong, Alex Chouldechova, Miro Dudík
  
  FAccT 2024 | January 2024
  
  DOI Publication Publication
- Unsupervised and semi-supervised bias benchmarking in face recognition
  
  Alex Chouldechova, Siqi Deng, Yongxin Wang, Wei Xia, Pietro Perona
  
  Computer Vision–ECCV 2022 | November 2022
  
  PDF
- Algorithmic fairness and vertical equity: Income fairness with IRS tax audit models
  
  Emily Black, Hadi Elzayn, Alex Chouldechova, Jacob Goldin, Daniel Ho
  
  2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
  
  Publication
- Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders
  
  Logan Stapleton, Min Hun Lee, Diana Qing, Marya Wright, Alex Chouldechova, Ken Holstein, Zhiwei Steven Wu, Haiyi Zhu
  
  2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
  
  PDF
- Human-algorithm collaboration: Achieving complementarity and avoiding unfairness
  
  Kate Donahue, Alex Chouldechova, Krishnaram Kenthapadi
  
  2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
  
  PDF
- The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies
  
  Riccardo Fogliato, Alex Chouldechova, Zachary Lipton
  
  ACM on Human-Computer Interaction | September 2021
  
  Publication
- Characterizing Fairness Over the Set of Good Models Under Selective Labels
  
  Amanda Coston, Ashesh Rambachan, Alex Chouldechova
  
  2021 International Conference on Machine Learning | July 2021
  
  PDF Publication
- On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes
  
  Riccardo Fogliato, Alice Xiang, Zachary Lipton, Daniel Nagin, Alex Chouldechova
  
  2021 AAAI/ACM Conference on AI, Ethics, and Society | May 2021
  
  Publication
- The effect of differential victim crime reporting on predictive policing systems
  
  Nil-Jana Akpinar, Maria De-Arteaga, Alex Chouldechova
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | March 2021
  
  DOI PDF
- Soliciting Stakeholders’ Fairness Notions in Child Maltreatment Predictive Systems
  
  Hao-Fei Cheng, Logan Stapleton, Ruiqi Wang, Paige Bullock, Alex Chouldechova, Zhiwei Steven Wu, Haiyi Zhu
  
  2021 Human Factors in Computing Systems | January 2021
  
  DOI Publication
- Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy
  
  Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alex Chouldechova, Daniel E. Ho
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | November 2020
  
  DOI Publication
- Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds
  
  Alan Mishler, Edward H. Kennedy, Alex Chouldechova
  
  2021 ACM Conference on Fairness, Accountability, and Transparency | September 2020
  
  DOI Publication
- Counterfactual predictions under runtime confounding
  
  Amanda Coston, Edward H. Kennedy, Alex Chouldechova
  
  2020 Neural Information Processing Systems | May 2020
  
  PDF
- Fairness Evaluation in Presence of Biased Noisy Labels
  
  Riccardo Fogliato, Max Grazier G'Sell, Alex Chouldechova
  
  International Conference on Artificial Intelligence and Statistics | March 2020
  
  Publication
- A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores
  
  Maria De-Arteaga, Riccardo Fogliato, Alex Chouldechova
  
  2020 Human Factors in Computing Systems | February 2020
  
  DOI Publication
- Toward Algorithmic Accountability in Public Services: A Qualitative Study of Affected Community Perspectives on Algorithmic Decision-making in Child Welfare Services
  
  Anna Brown, Alex Chouldechova, Emily Putnam-Hornstein, Andrew Tobin, Rhema Vaithianathan
  
  2019 Human Factors in Computing Systems | May 2019
  
  DOI PDF
- What’s in a Name? Reducing Bias in Bios without Access to Protected Attributes
  
  Alexey Romanov, Maria De-Arteaga, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alex Chouldechova, Sahin Geyik, krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai
  
  NAACL 2019 | April 2019
  
  Best Paper Award, NAACL 2019
  
  Publication
- Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting
  
  Maria De-Arteaga, Alexey Romanov, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alex Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
  
  FAT* ’19: Conference on Fairness, Accountability, and Transparency | January 2019
  
  PDF DOI Github
- Teach {IT}: Turning the Classroom into a Research Laboratory via Interactive E-Learning Tools
  
  Philipp Burckhardt, Alex Chouldechova, Rebecca Nugent
  
  International Conference on Teaching Statistics | March 2018
  
  PDF
- Does mitigating ML’s impact disparity require treatment disparity?
  
  Zachary Lipton, Julian McAuley, Alex Chouldechova
  
  2018 Neural Information Processing Systems | March 2018
  
  Publication
- A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions
  
  Alex Chouldechova, Diana Benavides-Prado, Oleksandr Fialko, Rhema Vaithianathan
  
  Conference on Fairness, Accountability and Transparency | January 2018
  
  PDF
- Taxonomizing Representational Harms using Speech Act Theory
  
  Emily Corvi, Hannah Washington, Stefanie Reed, Chad Atalla, Alex Chouldechova, Alex Dow, Jean Garcia-Gathright, Nick Pangakis, Emily Sheng, Dan Vann, Matthew Vogel, Hanna Wallach
  
  March 2025
  
  Publication
- A Shared Standard for Valid Measurement of Generative AI Systems’ Capabilities, Risks, and Impacts
  
  Alex Chouldechova, Chad Atalla, Solon Barocas, A. Feder Cooper, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Nick Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Matthew Vogel, Hannah Washington, Hanna Wallach
  
  December 2024
  
  Publication
- Gaps Between Research and Practice When Measuring Representational Harms Caused by LLM-Based Systems
  
  Emma Harvey, Emily Sheng, Su Lin Blodgett, Alex Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna Wallach
  
  November 2024
  
  Publication
- Dimensions of Generative AI Evaluation Design
  
  Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alex Chouldechova, Hanna Wallach
  
  November 2024
  
  Publication
- Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, Nick Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alex Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  November 2024
  
  Publication
- Doubting AI Predictions: Influence-Driven Second Opinion Recommendation
  
  Maria De-Arteaga, Alex Chouldechova, Artur Dubrawski
  
  April 2022
  
  PDF
- Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening
  
  Lingwei Cheng, Alex Chouldechova
  
  April 2022
  
  PDF
- Leveraging Expert Consistency to Improve Algorithmic Decision Support
  
  Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
  
  January 2021
  
  Publication
- The Present and Future of AI in Pre-Trial Risk Assessment Instruments
  
  Alex Chouldechova, Kristian Lum
  
  June 2020
  
  PDF
- The Frontiers of Fairness in Machine Learning
  
  Alex Chouldechova, Aaron Roth
  
  October 2018
  
  Publication
- Learning under selective labels in the presence of expert consistency
  
  Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
  
  July 2018
  
  Publication
- Fairer and more accurate, but for whom?
  
  Alex Chouldechova, Max Grazier G'Sell
  
  June 2017
  
  Publication
- Generalized Additive Model Selection
  
  Alex Chouldechova, Trevor Hastie
  
  June 2015
  
  Publication
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Published by Microsoft
  
  Publication Project Project
- SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation
  
  Lester Mackey, Miro Dudík, Alex Chouldechova
  
  October 2024
- Quality of life and functional status of patients treated with venovenous extracorporeal membrane oxygenation at 6 months
  
  Hussein D. Kanji, Alex Chouldechova, Samantha Harris-Fox, Juan J. Ronco, Ephraim O'dea, Chris Harvey, Constantin Shuster, Sonny Thiara, Giles J. Peek
  
  Journal of Critical Care | August 2021, Vol 66: pp. 26-30
  
  DOI Publication
- Hospital Injury Encounters of Children Identified by a Predictive Risk Model for Screening Child Maltreatment Referrals: Evidence From the Allegheny Family Screening Tool
  
  Rhema Vaithianathan, Emily Putnam-Hornstein, Alex Chouldechova, Diana Benavides-Prado, Rachel Berger
  
  JAMA Pediatrics | August 2020, Vol 174(11): pp. 1-6
  
  DOI Publication
- A group of industry, academic, and government experts convene in Philadelphia to explore the roots of algorithmic bias
  
  Alex Chouldechova, Aaron Roth
  
  Communications of the ACM | May 2020, Vol 63(5): pp. 82-89
  
  Publication
- A snapshot of the frontiers of fairness in machine learning
  
  Alex Chouldechova, Aaron Roth
  
  Communications of The ACM | April 2020, Vol 63(5): pp. 82-89
  
  DOI Publication
- Transparency and Simplicity in Criminal Risk Assessment
  
  Alex Chouldechova
  
  Harvard Data Science Review | March 2020, Vol 2(1)
  
  DOI Publication
- Safety and Outcomes of Mobile ECMO Using a Bicaval Dual-Stage Venous Catheter
  
  Hussein D. Kanji, Alex Chouldechova, Chris Harvey, Ephraim O'dea, Gail Faulkner, Giles J. Peek
  
  Asaio Journal | April 2017, Vol 63(3): pp. 351-355
  
  DOI Publication
- Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
  
  Alex Chouldechova
  
  Big Data | October 2016, Vol 5(2): pp. 153-163
  
  Publication
- Sequential selection procedures and false discovery rate control
  
  Max Grazier G'Sell, Stefan Wager, Alex Chouldechova, Robert Tibshirani
  
  Journal of The Royal Statistical Society Series B-statistical Methodology | February 2016, Vol 78(2): pp. 423-444
  
  DOI