{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:19:08Z","timestamp":1750220348072,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":27,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,7,21]],"date-time":"2021-07-21T00:00:00Z","timestamp":1626825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000781","name":"European Research Council","doi-asserted-by":"publisher","award":["789373"],"award-info":[{"award-number":["789373"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,7,21]]},"DOI":"10.1145\/3461702.3462630","type":"proceedings-article","created":{"date-parts":[[2021,7,31]],"date-time":"2021-07-31T01:21:32Z","timestamp":1627694492000},"page":"336-345","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Accounting for Model Uncertainty in Algorithmic Discrimination"],"prefix":"10.1145","author":[{"given":"Junaid","family":"Ali","sequence":"first","affiliation":[{"name":"Max Planck Institute for Software Systems, Saarbr\u00fccken, Germany"}]},{"given":"Preethi","family":"Lahoti","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Informatics, Saarbr\u00fccken, Germany"}]},{"given":"Krishna P.","family":"Gummadi","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Software Systems, Saarbr\u00fccken, Germany"}]}],"member":"320","published-online":{"date-parts":[[2021,7,30]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3306618.3314266"},{"key":"e_1_3_2_2_2_1","volume-title":"Counterfactual Accuracies for Alternative Models. ICLR Workshop on Machine Learning in Real Life Workshop","author":"Bhatt Umang","year":"2020","unstructured":"Umang Bhatt , Muhammad Bilal Zafar , Krishna Gummadi , and Adrian Weller . 2020 . Counterfactual Accuracies for Alternative Models. ICLR Workshop on Machine Learning in Real Life Workshop (2020). Umang Bhatt, Muhammad Bilal Zafar, Krishna Gummadi, and Adrian Weller. 2020. Counterfactual Accuracies for Alternative Models. ICLR Workshop on Machine Learning in Real Life Workshop (2020)."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"crossref","unstructured":"Leo Breiman et al. 2001. Statistical modeling: The two cultures (with comments and a rejoinder by the author). Statistical science Vol. 16 3 (2001) 199--231.  Leo Breiman et al. 2001. Statistical modeling: The two cultures (with comments and a rejoinder by the author). Statistical science Vol. 16 3 (2001) 199--231.","DOI":"10.1214\/ss\/1009213726"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"crossref","unstructured":"Sam Corbett-Davies Emma Pierson Avi Feller Sharad Goel and Aziz Huq. 2017. Algorithmic Decision Making and the Cost of Fairness. In KDD.  Sam Corbett-Davies Emma Pierson Avi Feller Sharad Goel and Aziz Huq. 2017. Algorithmic Decision Making and the Cost of Fairness. In KDD.","DOI":"10.1145\/3097983.3098095"},{"key":"e_1_3_2_2_5_1","volume-title":"International Conference on Machine Learning. PMLR, 1184--1193","author":"Depeweg Stefan","year":"2018","unstructured":"Stefan Depeweg , Jose-Miguel Hernandez-Lobato , Finale Doshi-Velez , and Steffen Udluft . 2018 . Decomposition of uncertainty in Bayesian deep learning for efficient and risk-sensitive learning . In International Conference on Machine Learning. PMLR, 1184--1193 . Stefan Depeweg, Jose-Miguel Hernandez-Lobato, Finale Doshi-Velez, and Steffen Udluft. 2018. Decomposition of uncertainty in Bayesian deep learning for efficient and risk-sensitive learning. In International Conference on Machine Learning. PMLR, 1184--1193."},{"key":"e_1_3_2_2_6_1","volume-title":"Aleatory or epistemic? Does it matter? Structural safety","author":"Kiureghian Armen Der","year":"2009","unstructured":"Armen Der Kiureghian and Ove Ditlevsen . 2009. Aleatory or epistemic? Does it matter? Structural safety , Vol. 31 , 2 ( 2009 ), 105--112. Armen Der Kiureghian and Ove Ditlevsen. 2009. Aleatory or epistemic? Does it matter? Structural safety, Vol. 31, 2 (2009), 105--112."},{"key":"e_1_3_2_2_7_1","first-page":"1","article-title":"CVXPY: A Python-Embedded Modeling Language for Convex Optimization","volume":"17","author":"Diamond Steven","year":"2016","unstructured":"Steven Diamond and Stephen Boyd . 2016 . CVXPY: A Python-Embedded Modeling Language for Convex Optimization . Journal of Machine Learning Research , Vol. 17 , 83 (2016), 1 -- 5 . Steven Diamond and Stephen Boyd. 2016. CVXPY: A Python-Embedded Modeling Language for Convex Optimization. Journal of Machine Learning Research, Vol. 17, 83 (2016), 1--5.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_2_8_1","volume-title":"Variable Importance Clouds: A Way to Explore Variable Importance for the Set of Good Models. arXiv preprint arXiv:1901.03209","author":"Dong Jiayun","year":"2019","unstructured":"Jiayun Dong and Cynthia Rudin . 2019. Variable Importance Clouds: A Way to Explore Variable Importance for the Set of Good Models. arXiv preprint arXiv:1901.03209 ( 2019 ). Jiayun Dong and Cynthia Rudin. 2019. Variable Importance Clouds: A Way to Explore Variable Importance for the Set of Good Models. arXiv preprint arXiv:1901.03209 (2019)."},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"crossref","unstructured":"Cynthia Dwork Moritz Hardt Toniann Pitassi and Omer Reingold. 2012. Fairness Through Awareness. In ITCSC.  Cynthia Dwork Moritz Hardt Toniann Pitassi and Omer Reingold. 2012. Fairness Through Awareness. In ITCSC.","DOI":"10.1145\/2090236.2090255"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"crossref","unstructured":"Michael Feldman Sorelle A. Friedler John Moeller Carlos Scheidegger and Suresh Venkatasubramanian. 2015. Certifying and Removing Disparate Impact. In KDD.  Michael Feldman Sorelle A. Friedler John Moeller Carlos Scheidegger and Suresh Venkatasubramanian. 2015. Certifying and Removing Disparate Impact. In KDD.","DOI":"10.1145\/2783258.2783311"},{"key":"e_1_3_2_2_11_1","first-page":"1","article-title":"All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously","volume":"20","author":"Fisher Aaron","year":"2019","unstructured":"Aaron Fisher , Cynthia Rudin , and Francesca Dominici . 2019 . All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously . Journal of Machine Learning Research , Vol. 20 , 177 (2019), 1 -- 81 . Aaron Fisher, Cynthia Rudin, and Francesca Dominici. 2019. All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously. Journal of Machine Learning Research, Vol. 20, 177 (2019), 1--81.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_2_12_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"32","author":"Nina","year":"2018","unstructured":"Nina Grgi\u0107-Hlavc a, Muhammad Bilal Zafar , Krishna P Gummadi , and Adrian Weller . 2018 . Beyond distributive fairness in algorithmic decision making: Feature selection for procedurally fair learning . In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 32 . Nina Grgi\u0107-Hlavc a, Muhammad Bilal Zafar, Krishna P Gummadi, and Adrian Weller. 2018. Beyond distributive fairness in algorithmic decision making: Feature selection for procedurally fair learning. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 32."},{"key":"e_1_3_2_2_13_1","unstructured":"Moritz Hardt Eric Price and Nathan Srebro. 2016. Equality of Opportunity in Supervised Learning. In NIPS.  Moritz Hardt Eric Price and Nathan Srebro. 2016. Equality of Opportunity in Supervised Learning. In NIPS."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0951-8320(96)00077-4"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-021-05946-3"},{"key":"e_1_3_2_2_16_1","volume-title":"What uncertainties do we need in bayesian deep learning for computer vision? arXiv preprint arXiv:1703.04977","author":"Kendall Alex","year":"2017","unstructured":"Alex Kendall and Yarin Gal . 2017. What uncertainties do we need in bayesian deep learning for computer vision? arXiv preprint arXiv:1703.04977 ( 2017 ). Alex Kendall and Yarin Gal. 2017. What uncertainties do we need in bayesian deep learning for computer vision? arXiv preprint arXiv:1703.04977 (2017)."},{"key":"e_1_3_2_2_17_1","volume-title":"Lin (Eds.)","volume":"33","author":"Lahoti Preethi","year":"2020","unstructured":"Preethi Lahoti , Alex Beutel , Jilin Chen , Kang Lee , Flavien Prost , Nithum Thain , Xuezhi Wang , and Ed Chi . 2020 . Fairness without Demographics through Adversarially Reweighted Learning. In Advances in Neural Information Processing Systems, H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, and H . Lin (Eds.) , Vol. 33 . Curran Associates, Inc., 728--740. Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, and Ed Chi. 2020. Fairness without Demographics through Adversarially Reweighted Learning. In Advances in Neural Information Processing Systems, H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, and H. Lin (Eds.), Vol. 33. Curran Associates, Inc., 728--740."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.14778\/3372716.3372723"},{"key":"e_1_3_2_2_19_1","unstructured":"Jeff Larson Surya Mattu Lauren Kirchner and Julia Angwin. 2016. Data and analysis for `How we analyzed the COMPAS recidivism algorithm'. https:\/\/github.com\/propublica\/compas-analysis.  Jeff Larson Surya Mattu Lauren Kirchner and Julia Angwin. 2016. Data and analysis for `How we analyzed the COMPAS recidivism algorithm'. https:\/\/github.com\/propublica\/compas-analysis."},{"key":"e_1_3_2_2_21_1","volume-title":"Flavio du Pin Calmon, and Berk Ustun","author":"Marx Charles T","year":"2019","unstructured":"Charles T Marx , Flavio du Pin Calmon, and Berk Ustun . 2019 . Predictive multiplicity in classification. arXiv preprint arXiv:1909.06677 (2019). Charles T Marx, Flavio du Pin Calmon, and Berk Ustun. 2019. Predictive multiplicity in classification. arXiv preprint arXiv:1909.06677 (2019)."},{"key":"e_1_3_2_2_23_1","volume-title":"Conference on Uncertainty in Artificial Intelligence. PMLR, 809--818","author":"Pawelczyk Martin","year":"2020","unstructured":"Martin Pawelczyk , Klaus Broelemann , and Gjergji Kasneci . 2020 . On Counterfactual Explanations under Predictive Multiplicity . In Conference on Uncertainty in Artificial Intelligence. PMLR, 809--818 . Martin Pawelczyk, Klaus Broelemann, and Gjergji Kasneci. 2020. On Counterfactual Explanations under Predictive Multiplicity. In Conference on Uncertainty in Artificial Intelligence. PMLR, 809--818."},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"crossref","unstructured":"Dino Pedreschi Salvatore Ruggieri and Franco Turini. 2008. Discrimination-aware Data Mining. In KDD.  Dino Pedreschi Salvatore Ruggieri and Franco Turini. 2008. Discrimination-aware Data Mining. In KDD.","DOI":"10.1145\/1401890.1401959"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220046"},{"key":"e_1_3_2_2_26_1","unstructured":"Muhammad Bilal Zafar Isabel Valera Manuel Rodriguez Krishna P. Gummadi and Adrian Weller. 2017c. From Parity to Preference-based Notions of Fairness in Classification. In NIPS.  Muhammad Bilal Zafar Isabel Valera Manuel Rodriguez Krishna P. Gummadi and Adrian Weller. 2017c. From Parity to Preference-based Notions of Fairness in Classification. In NIPS."},{"key":"e_1_3_2_2_27_1","volume-title":"Manuel Gomez Rodriguez, and Krishna P. Gummadi","author":"Zafar Muhammad Bilal","year":"2017","unstructured":"Muhammad Bilal Zafar , Isabel Valera , Manuel Gomez Rodriguez, and Krishna P. Gummadi . 2017 a. Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment. In WWW. Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, and Krishna P. Gummadi. 2017a. Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment. In WWW."},{"key":"e_1_3_2_2_28_1","volume-title":"Manuel Gomez Rodriguez, and Krishna P. Gummadi","author":"Zafar Muhammad Bilal","year":"2017","unstructured":"Muhammad Bilal Zafar , Isabel Valera , Manuel Gomez Rodriguez, and Krishna P. Gummadi . 2017 b. Fairness Constraints : Mechanisms for Fair Classification. In AISTATS. Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, and Krishna P. Gummadi. 2017b. Fairness Constraints: Mechanisms for Fair Classification. In AISTATS."},{"key":"e_1_3_2_2_29_1","unstructured":"R. Zemel Y. Wu K. Swersky T. Pitassi and C. Dwork. 2013. Learning Fair Representations. In ICML.  R. Zemel Y. Wu K. Swersky T. Pitassi and C. Dwork. 2013. Learning Fair Representations. In ICML."}],"event":{"name":"AIES '21: AAAI\/ACM Conference on AI, Ethics, and Society","sponsor":["SIGAI ACM Special Interest Group on Artificial Intelligence","AAAI"],"location":"Virtual Event USA","acronym":"AIES '21"},"container-title":["Proceedings of the 2021 AAAI\/ACM Conference on AI, Ethics, and Society"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3461702.3462630","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3461702.3462630","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:17:06Z","timestamp":1750191426000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3461702.3462630"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,21]]},"references-count":27,"alternative-id":["10.1145\/3461702.3462630","10.1145\/3461702"],"URL":"https:\/\/doi.org\/10.1145\/3461702.3462630","relation":{},"subject":[],"published":{"date-parts":[[2021,7,21]]},"assertion":[{"value":"2021-07-30","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}