A structured regression approach for evaluating model performance across intersectional subgroups
Christine Herlihy, Kimberly Truong, Alex Chouldechova, Miro Dudík
FAccT 2024 | January 2024
Alex Chouldechova
Principal Researcher
Publications
Publications by Year
-
-
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
Human-algorithm collaboration: Achieving complementarity and avoiding unfairness
Kate Donahue, Alex Chouldechova, Krishnaram Kenthapadi
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
Doubting AI Predictions: Influence-Driven Second Opinion Recommendation
Maria De-Arteaga, Alex Chouldechova, Artur Dubrawski
April 2022
Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening
Lingwei Cheng, Alex Chouldechova
April 2022
-
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
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
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
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
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
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
The Present and Future of AI in Pre-Trial Risk Assessment Instruments
Alex Chouldechova, Kristian Lum
June 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, Vol 63(5): pp. 82-89
Counterfactual predictions under runtime confounding
Amanda Coston, Edward H. Kennedy, Alex Chouldechova
2020 Neural Information Processing Systems | May 2020
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
Transparency and Simplicity in Criminal Risk Assessment
Harvard Data Science Review | March 2020, Vol 2(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
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
-
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
Does mitigating ML’s impact disparity require treatment disparity?
Zachary Lipton, Julian McAuley, Alex Chouldechova
2018 Neural Information Processing Systems | March 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
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
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
-
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Big Data | October 2016, Vol 5(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, Vol 78(2): pp. 423-444
-
Generalized Additive Model Selection
Alex Chouldechova, Trevor Hastie
June 2015
Publications by Research Area
-
A structured regression approach for evaluating model performance across intersectional subgroups
Christine Herlihy, Kimberly Truong, Alex Chouldechova, Miro Dudík
FAccT 2024 | January 2024
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
Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening
Lingwei Cheng, Alex Chouldechova
April 2022
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
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
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
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
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
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
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
-
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, Vol 63(5): pp. 82-89
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
Transparency and Simplicity in Criminal Risk Assessment
Harvard Data Science Review | March 2020, Vol 2(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
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, Vol 5(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, Vol 78(2): pp. 423-444
Generalized Additive Model Selection
Alex Chouldechova, Trevor Hastie
June 2015
-
Human-algorithm collaboration: Achieving complementarity and avoiding unfairness
Kate Donahue, Alex Chouldechova, Krishnaram Kenthapadi
2022 ACM Conference on Fairness, Accountability, and Transparency | June 2022
Doubting AI Predictions: Influence-Driven Second Opinion Recommendation
Maria De-Arteaga, Alex Chouldechova, Artur Dubrawski
April 2022
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
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
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
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
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
-
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
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
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
-
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, Vol 5(2): pp. 153-163
-
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
-
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
Publications by Type
-
A structured regression approach for evaluating model performance across intersectional subgroups
Christine Herlihy, Kimberly Truong, Alex Chouldechova, Miro Dudík
FAccT 2024 | January 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
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
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
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 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
Counterfactual predictions under runtime confounding
Amanda Coston, Edward H. Kennedy, Alex Chouldechova
2020 Neural Information Processing Systems | May 2020
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
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
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
-
Doubting AI Predictions: Influence-Driven Second Opinion Recommendation
Maria De-Arteaga, Alex Chouldechova, Artur Dubrawski
April 2022
Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening
Lingwei Cheng, Alex Chouldechova
April 2022
Leveraging Expert Consistency to Improve Algorithmic Decision Support
Maria De-Arteaga, Artur Dubrawski, Alex Chouldechova
January 2021
The Present and Future of AI in Pre-Trial Risk Assessment Instruments
Alex Chouldechova, Kristian Lum
June 2020
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
Fairer and more accurate, but for whom?
Alex Chouldechova, Max Grazier G'Sell
June 2017
Generalized Additive Model Selection
Alex Chouldechova, Trevor Hastie
June 2015
-
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
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
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
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
Transparency and Simplicity in Criminal Risk Assessment
Harvard Data Science Review | March 2020, Vol 2(1)
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
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Big Data | October 2016, Vol 5(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, Vol 78(2): pp. 423-444