Comparison requires valid measurement: Rethinking attack success rate comparisons in AI red teaming
Alex Chouldechova, A. Feder Cooper, Solon Barocas, Abhinav Palia, Dan Vann, Hanna Wallach
NeurIPS 2025 | October 2025
Alex Chouldechova
Senior Principal Researcher
출판물
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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
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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
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Validating LLM-as-a-Judge Systems under Rating Indeterminacy
Luke Guerdan, Solon Barocas, Kenneth Holstein, Hanna Wallach, Zhiwei Steven Wu, Alex Chouldechova
NeurIPS 2025 | March 2025
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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
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Machine Unlearning Doesn’t Do What You Think: Lessons for Generative AI Policy, Research, and Practice
A. F. Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alex Chouldechova, Jamie Hayes, Yangsibo Huang, Niloofar Mireshghallah, Ilia Shumailov, Eleni Triantafillou, Peter Kairouz, N. Mitchell, Percy Liang, Daniel E. Ho, Yejin Choi, Sanmi Koyejo, Fernando Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, A. Cyphert, Mark A. Lemley, danah boyd, Jennifer Wortman Vaughan, M. Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna Wallach, Nicolas Papernot, Katherine Lee
NeurIPS 2025 | December 2024
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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
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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
글쓴이 Microsoft
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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
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Dimensions of Generative AI Evaluation Design
Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alex Chouldechova, Hanna Wallach
November 2024
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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
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SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation
Lester Mackey, Miro Dudík, Alex Chouldechova
October 2024
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A structured regression approach for evaluating model performance across intersectional subgroups
Christine Herlihy, Kimberly Truong, Alex Chouldechova, Miro Dudík
FAccT 2024 | January 2024
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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
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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
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Human-algorithm collaboration: Achieving complementarity and avoiding unfairness
Kate Donahue, Alex Chouldechova, Krishnaram Kenthapadi
2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
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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
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Doubting AI Predictions: Influence-Driven Second Opinion Recommendation
Maria De-Arteaga, Alex Chouldechova, Artur Dubrawski
April 2022
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Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening
Lingwei Cheng, Alex Chouldechova
April 2022
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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
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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, 제 66 권: pp. 26-30
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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
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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
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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
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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
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Leveraging Expert Consistency to Improve Algorithmic Decision Support
Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
January 2021
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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
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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
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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, 제 174 권(11): pp. 1-6
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The Present and Future of AI in Pre-Trial Risk Assessment Instruments
Alex Chouldechova, Kristian Lum
June 2020
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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, 제 63 권(5): pp. 82-89
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Counterfactual predictions under runtime confounding
Amanda Coston, Edward H. Kennedy, Alex Chouldechova
2020 Neural Information Processing Systems | May 2020
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A snapshot of the frontiers of fairness in machine learning
Alex Chouldechova, Aaron Roth
Communications of The ACM | April 2020, 제 63 권(5): pp. 82-89
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Transparency and Simplicity in Criminal Risk Assessment
Harvard Data Science Review | March 2020, 제 2 권(1)
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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
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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
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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
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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
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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
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The Frontiers of Fairness in Machine Learning
Alex Chouldechova, Aaron Roth
October 2018
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Learning under selective labels in the presence of expert consistency
Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
July 2018
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Does mitigating ML’s impact disparity require treatment disparity?
Zachary Lipton, Julian McAuley, Alex Chouldechova
2018 Neural Information Processing Systems | March 2018
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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
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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
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Fairer and more accurate, but for whom?
Alex Chouldechova, Max Grazier G'Sell
June 2017
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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, 제 63 권(3): pp. 351-355
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Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Big Data | October 2016, 제 5 권(2): pp. 153-163
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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, 제 78 권(2): pp. 423-444
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Generalized Additive Model Selection
Alex Chouldechova, Trevor Hastie
June 2015
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Comparison requires valid measurement: Rethinking attack success rate comparisons in AI red teaming
Alex Chouldechova, A. Feder Cooper, Solon Barocas, Abhinav Palia, Dan Vann, Hanna Wallach
NeurIPS 2025 | October 2025
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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
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Validating LLM-as-a-Judge Systems under Rating Indeterminacy
Luke Guerdan, Solon Barocas, Kenneth Holstein, Hanna Wallach, Zhiwei Steven Wu, Alex Chouldechova
NeurIPS 2025 | March 2025
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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
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Machine Unlearning Doesn’t Do What You Think: Lessons for Generative AI Policy, Research, and Practice
A. F. Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alex Chouldechova, Jamie Hayes, Yangsibo Huang, Niloofar Mireshghallah, Ilia Shumailov, Eleni Triantafillou, Peter Kairouz, N. Mitchell, Percy Liang, Daniel E. Ho, Yejin Choi, Sanmi Koyejo, Fernando Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, A. Cyphert, Mark A. Lemley, danah boyd, Jennifer Wortman Vaughan, M. Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna Wallach, Nicolas Papernot, Katherine Lee
NeurIPS 2025 | December 2024
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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
글쓴이 Microsoft
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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
-
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
-
Dimensions of Generative AI Evaluation Design
Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alex Chouldechova, Hanna Wallach
November 2024
-
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
-
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
-
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
-
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
-
Human-algorithm collaboration: Achieving complementarity and avoiding unfairness
Kate Donahue, Alex Chouldechova, Krishnaram Kenthapadi
2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
-
Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening
Lingwei Cheng, Alex Chouldechova
April 2022
-
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
-
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
-
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
-
Leveraging Expert Consistency to Improve Algorithmic Decision Support
Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
January 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, Alex Chouldechova, Daniel E. Ho
2021 ACM Conference on Fairness, Accountability, and Transparency | November 2020
-
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
-
The Present and Future of AI in Pre-Trial Risk Assessment Instruments
Alex Chouldechova, Kristian Lum
June 2020
-
Counterfactual predictions under runtime confounding
Amanda Coston, Edward H. Kennedy, Alex Chouldechova
2020 Neural Information Processing Systems | May 2020
-
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, 제 63 권(5): pp. 82-89
-
A snapshot of the frontiers of fairness in machine learning
Alex Chouldechova, Aaron Roth
Communications of The ACM | April 2020, 제 63 권(5): pp. 82-89
-
Transparency and Simplicity in Criminal Risk Assessment
Harvard Data Science Review | March 2020, 제 2 권(1)
-
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
-
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
-
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
-
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
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The Frontiers of Fairness in Machine Learning
Alex Chouldechova, Aaron Roth
October 2018
-
Learning under selective labels in the presence of expert consistency
Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
July 2018
-
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
-
Does mitigating ML’s impact disparity require treatment disparity?
Zachary Lipton, Julian McAuley, Alex Chouldechova
2018 Neural Information Processing Systems | March 2018
-
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
-
Fairer and more accurate, but for whom?
Alex Chouldechova, Max Grazier G'Sell
June 2017
-
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Big Data | October 2016, 제 5 권(2): pp. 153-163
-
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, 제 78 권(2): pp. 423-444
-
Generalized Additive Model Selection
Alex Chouldechova, Trevor Hastie
June 2015
-
-
-
Comparison requires valid measurement: Rethinking attack success rate comparisons in AI red teaming
Alex Chouldechova, A. Feder Cooper, Solon Barocas, Abhinav Palia, Dan Vann, Hanna Wallach
NeurIPS 2025 | October 2025
-
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
글쓴이 Microsoft
-
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
-
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Big Data | October 2016, 제 5 권(2): pp. 153-163
-
-
-
Comparison requires valid measurement: Rethinking attack success rate comparisons in AI red teaming
Alex Chouldechova, A. Feder Cooper, Solon Barocas, Abhinav Palia, Dan Vann, Hanna Wallach
NeurIPS 2025 | October 2025
-
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
-
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
-
-
-
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
-
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
-
-
-
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
-
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
-
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
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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
글쓴이 Microsoft
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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
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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
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Dimensions of Generative AI Evaluation Design
Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alex Chouldechova, Hanna Wallach
November 2024
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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
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A structured regression approach for evaluating model performance across intersectional subgroups
Christine Herlihy, Kimberly Truong, Alex Chouldechova, Miro Dudík
FAccT 2024 | January 2024
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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
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Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening
Lingwei Cheng, Alex Chouldechova
April 2022
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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
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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
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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
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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, 제 174 권(11): pp. 1-6
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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
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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
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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
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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
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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
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Fairer and more accurate, but for whom?
Alex Chouldechova, Max Grazier G'Sell
June 2017
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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
글쓴이 Microsoft
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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
글쓴이 Microsoft
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Human-algorithm collaboration: Achieving complementarity and avoiding unfairness
Kate Donahue, Alex Chouldechova, Krishnaram Kenthapadi
2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
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Doubting AI Predictions: Influence-Driven Second Opinion Recommendation
Maria De-Arteaga, Alex Chouldechova, Artur Dubrawski
April 2022
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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
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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
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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
-
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
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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
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Leveraging Expert Consistency to Improve Algorithmic Decision Support
Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
January 2021
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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
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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
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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
글쓴이 Microsoft
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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, 제 66 권: pp. 26-30
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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, 제 174 권(11): pp. 1-6
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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, 제 63 권(3): pp. 351-355
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Comparison requires valid measurement: Rethinking attack success rate comparisons in AI red teaming
Alex Chouldechova, A. Feder Cooper, Solon Barocas, Abhinav Palia, Dan Vann, Hanna Wallach
NeurIPS 2025 | October 2025
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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
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Validating LLM-as-a-Judge Systems under Rating Indeterminacy
Luke Guerdan, Solon Barocas, Kenneth Holstein, Hanna Wallach, Zhiwei Steven Wu, Alex Chouldechova
NeurIPS 2025 | March 2025
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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
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Machine Unlearning Doesn’t Do What You Think: Lessons for Generative AI Policy, Research, and Practice
A. F. Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alex Chouldechova, Jamie Hayes, Yangsibo Huang, Niloofar Mireshghallah, Ilia Shumailov, Eleni Triantafillou, Peter Kairouz, N. Mitchell, Percy Liang, Daniel E. Ho, Yejin Choi, Sanmi Koyejo, Fernando Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, A. Cyphert, Mark A. Lemley, danah boyd, Jennifer Wortman Vaughan, M. Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna Wallach, Nicolas Papernot, Katherine Lee
NeurIPS 2025 | December 2024
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A structured regression approach for evaluating model performance across intersectional subgroups
Christine Herlihy, Kimberly Truong, Alex Chouldechova, Miro Dudík
FAccT 2024 | January 2024
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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
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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
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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
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Human-algorithm collaboration: Achieving complementarity and avoiding unfairness
Kate Donahue, Alex Chouldechova, Krishnaram Kenthapadi
2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
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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
-
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
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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
-
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
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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
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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
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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
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Counterfactual predictions under runtime confounding
Amanda Coston, Edward H. Kennedy, Alex Chouldechova
2020 Neural Information Processing Systems | May 2020
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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
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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
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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
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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
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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
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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
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Does mitigating ML’s impact disparity require treatment disparity?
Zachary Lipton, Julian McAuley, Alex Chouldechova
2018 Neural Information Processing Systems | March 2018
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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
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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
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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
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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
-
Dimensions of Generative AI Evaluation Design
Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alex Chouldechova, Hanna Wallach
November 2024
-
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
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Doubting AI Predictions: Influence-Driven Second Opinion Recommendation
Maria De-Arteaga, Alex Chouldechova, Artur Dubrawski
April 2022
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Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening
Lingwei Cheng, Alex Chouldechova
April 2022
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Leveraging Expert Consistency to Improve Algorithmic Decision Support
Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
January 2021
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The Present and Future of AI in Pre-Trial Risk Assessment Instruments
Alex Chouldechova, Kristian Lum
June 2020
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The Frontiers of Fairness in Machine Learning
Alex Chouldechova, Aaron Roth
October 2018
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Learning under selective labels in the presence of expert consistency
Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
July 2018
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Fairer and more accurate, but for whom?
Alex Chouldechova, Max Grazier G'Sell
June 2017
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Generalized Additive Model Selection
Alex Chouldechova, Trevor Hastie
June 2015
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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
글쓴이 Microsoft
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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, 제 66 권: pp. 26-30
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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, 제 174 권(11): pp. 1-6
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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, 제 63 권(5): pp. 82-89
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A snapshot of the frontiers of fairness in machine learning
Alex Chouldechova, Aaron Roth
Communications of The ACM | April 2020, 제 63 권(5): pp. 82-89
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Transparency and Simplicity in Criminal Risk Assessment
Harvard Data Science Review | March 2020, 제 2 권(1)
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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, 제 63 권(3): pp. 351-355
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Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Big Data | October 2016, 제 5 권(2): pp. 153-163
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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, 제 78 권(2): pp. 423-444
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