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Alexandra Chouldechova
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2020 – today
- 2022
- [i21]Kate Donahue, Alexandra Chouldechova, Krishnaram Kenthapadi:
Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness. CoRR abs/2202.08821 (2022) - [i20]Lingwei Cheng, Alexandra Chouldechova:
Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening. CoRR abs/2204.05478 (2022) - [i19]Maria De-Arteaga, Alexandra Chouldechova, Artur Dubrawski:
Doubting AI Predictions: Influence-Driven Second Opinion Recommendation. CoRR abs/2205.00072 (2022) - 2021
- [j4]Rhema Vaithianathan, Diana Benavides Prado
, Eric E. Dalton, Alexandra Chouldechova, Emily Putnam-Hornstein:
Using a Machine Learning Tool to Support High-Stakes Decisions in Child Protection. AI Mag. 42(1): 53-60 (2021) - [j3]Riccardo Fogliato, Alexandra Chouldechova, Zachary C. Lipton:
The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies. Proc. ACM Hum. Comput. Interact. 5(CSCW2): 1-24 (2021) - [c16]Riccardo Fogliato, Alice Xiang, Zachary C. Lipton, Daniel Nagin, Alexandra Chouldechova:
On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes. AIES 2021: 100-111 - [c15]Hao Fei Cheng, Logan Stapleton, Ruiqi Wang, Paige Bullock, Alexandra Chouldechova, Zhiwei Steven Wu, Haiyi Zhu:
Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systems. CHI 2021: 390:1-390:17 - [c14]Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alexandra Chouldechova, Daniel E. Ho:
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy. FAccT 2021: 173-184 - [c13]Alan Mishler
, Edward H. Kennedy, Alexandra Chouldechova:
Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds. FAccT 2021: 386-400 - [c12]Nil-Jana Akpinar, Maria De-Arteaga, Alexandra Chouldechova:
The effect of differential victim crime reporting on predictive policing systems. FAccT 2021: 838-849 - [c11]Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova:
Characterizing Fairness Over the Set of Good Models Under Selective Labels. ICML 2021: 2144-2155 - [i18]Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova:
Characterizing Fairness Over the Set of Good Models Under Selective Labels. CoRR abs/2101.00352 (2021) - [i17]Maria De-Arteaga, Artur Dubrawski, Alexandra Chouldechova:
Leveraging Expert Consistency to Improve Algorithmic Decision Support. CoRR abs/2101.09648 (2021) - [i16]Nil-Jana Akpinar, Maria De-Arteaga, Alexandra Chouldechova:
The effect of differential victim crime reporting on predictive policing systems. CoRR abs/2102.00128 (2021) - [i15]Hao Fei Cheng, Logan Stapleton, Ruiqi Wang, Paige Bullock, Alexandra Chouldechova, Zhiwei Steven Wu, Haiyi Zhu:
Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systems. CoRR abs/2102.01196 (2021) - [i14]Riccardo Fogliato, Alexandra Chouldechova, Zachary C. Lipton:
The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies. CoRR abs/2109.01443 (2021) - 2020
- [j2]Alexandra Chouldechova, Aaron Roth:
A snapshot of the frontiers of fairness in machine learning. Commun. ACM 63(5): 82-89 (2020) - [c10]Riccardo Fogliato, Alexandra Chouldechova, Max G'Sell:
Fairness Evaluation in Presence of Biased Noisy Labels. AISTATS 2020: 2325-2336 - [c9]Maria De-Arteaga, Riccardo Fogliato, Alexandra Chouldechova:
A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores. CHI 2020: 1-12 - [c8]Amanda Coston, Alan Mishler
, Edward H. Kennedy, Alexandra Chouldechova:
Counterfactual risk assessments, evaluation, and fairness. FAT* 2020: 582-593 - [c7]Amanda Coston, Edward H. Kennedy, Alexandra Chouldechova:
Counterfactual Predictions under Runtime Confounding. NeurIPS 2020 - [i13]Maria De-Arteaga, Riccardo Fogliato, Alexandra Chouldechova:
A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores. CoRR abs/2002.08035 (2020) - [i12]Riccardo Fogliato, Max G'Sell, Alexandra Chouldechova:
Fairness Evaluation in Presence of Biased Noisy Labels. CoRR abs/2003.13808 (2020) - [i11]Amanda Coston, Edward H. Kennedy, Alexandra Chouldechova:
Counterfactual Predictions under Runtime Confounding. CoRR abs/2006.16916 (2020) - [i10]Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alexandra Chouldechova, Daniel E. Ho:
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy. CoRR abs/2011.07194 (2020)
2010 – 2019
- 2019
- [c6]Anna Brown, Alexandra Chouldechova, Emily Putnam-Hornstein
, Andrew Tobin, Rhema Vaithianathan:
Toward Algorithmic Accountability in Public Services: A Qualitative Study of Affected Community Perspectives on Algorithmic Decision-making in Child Welfare Services. CHI 2019: 41 - [c5]Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs
, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai:
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. FAT 2019: 120-128 - [c4]Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Kalai:
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. NAACL-HLT (1) 2019: 4187-4195 - [i9]Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai:
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. CoRR abs/1901.09451 (2019) - [i8]Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai:
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. CoRR abs/1904.05233 (2019) - [i7]Amanda Coston, Alexandra Chouldechova, Edward H. Kennedy:
Counterfactual Risk Assessments, Evaluation, and Fairness. CoRR abs/1909.00066 (2019) - 2018
- [c3]Alexandra Chouldechova, Diana Benavides Prado
, Oleksandr Fialko, Rhema Vaithianathan:
A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions. FAT 2018: 134-148 - [c2]Zachary C. Lipton, Julian J. McAuley, Alexandra Chouldechova:
Does mitigating ML's impact disparity require treatment disparity? NeurIPS 2018: 8136-8146 - [i6]Maria De-Arteaga, Artur Dubrawski, Alexandra Chouldechova:
Learning under selective labels in the presence of expert consistency. CoRR abs/1807.00905 (2018) - [i5]Alexandra Chouldechova, Aaron Roth:
The Frontiers of Fairness in Machine Learning. CoRR abs/1810.08810 (2018) - 2017
- [j1]Alexandra Chouldechova:
Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments. Big Data 5(2): 153-163 (2017) - [i4]Alexandra Chouldechova:
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments. CoRR abs/1703.00056 (2017) - [i3]Alexandra Chouldechova, Max G'Sell:
Fairer and more accurate, but for whom? CoRR abs/1707.00046 (2017) - [i2]Zachary C. Lipton, Alexandra Chouldechova, Julian J. McAuley:
Does mitigating ML's disparate impact require disparate treatment? CoRR abs/1711.07076 (2017) - 2016
- [i1]Alexandra Chouldechova:
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments. CoRR abs/1610.07524 (2016) - 2013
- [c1]Alexandra Chouldechova, David Mease:
Differences in search engine evaluations between query owners and non-owners. WSDM 2013: 103-112
Coauthor Index

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