{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T09:16:31Z","timestamp":1766049391302,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,6,15]],"date-time":"2020-06-15T00:00:00Z","timestamp":1592179200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,6,15]]},"DOI":"10.1145\/3378393.3402507","type":"proceedings-article","created":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T16:22:23Z","timestamp":1593620543000},"page":"97-104","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["The Role of In-Group Bias and Balanced Data"],"prefix":"10.1145","author":[{"given":"Arpita","family":"Biswas","sequence":"first","affiliation":[{"name":"Indian Institute of Science, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marta","family":"Kolczynska","sequence":"additional","affiliation":[{"name":"Institute of Political Studies of the Polish Academy of Sciences, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saana","family":"Rantanen","sequence":"additional","affiliation":[{"name":"University of Turku, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Polina","family":"Rozenshtein","sequence":"additional","affiliation":[{"name":"Institute of Data Science, National University of Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,7]]},"reference":[{"volume-title":"The new Jim Crow: Mass incarceration in the age of colorblindness","author":"Alexander Michelle","key":"e_1_3_2_1_1_1","unstructured":"Michelle Alexander . 2010. The new Jim Crow: Mass incarceration in the age of colorblindness . The New Press , New York, NY . Michelle Alexander. 2010. The new Jim Crow: Mass incarceration in the age of colorblindness. The New Press, New York, NY."},{"key":"e_1_3_2_1_2_1","first-page":"671","article-title":"Big Data's Disparate Impact","volume":"104","author":"Barocas Solon","year":"2016","unstructured":"Solon Barocas and Andrew Selbst . 2016 . Big Data's Disparate Impact . California Law Review 104 , 1 (2016), 671 -- 732 . https:\/\/doi.org\/10.15779\/Z38BG31 10.15779\/Z38BG31 Solon Barocas and Andrew Selbst. 2016. Big Data's Disparate Impact. California Law Review 104, 1 (2016), 671--732. https:\/\/doi.org\/10.15779\/Z38BG31","journal-title":"California Law Review"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1177\/0049124118782533"},{"key":"e_1_3_2_1_4_1","volume-title":"Proceedings of the 1st Conference on Fairness, Accountability and Transparency, Sorelle A. Friedler and Christo Wilson (Eds.)","volume":"81","author":"Buolamwini Joy","year":"2018","unstructured":"Joy Buolamwini and Timnit Gebru . 2018 . Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classificatio . In Proceedings of the 1st Conference on Fairness, Accountability and Transparency, Sorelle A. Friedler and Christo Wilson (Eds.) , Vol. 81 . New York, 77--91. https:\/\/doi.org\/10.2147\/OTT.S126905 10.2147\/OTT.S126905 Joy Buolamwini and Timnit Gebru. 2018. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classificatio. In Proceedings of the 1st Conference on Fairness, Accountability and Transparency, Sorelle A. Friedler and Christo Wilson (Eds.), Vol. 81. New York, 77--91. https:\/\/doi.org\/10.2147\/OTT.S126905"},{"key":"e_1_3_2_1_5_1","volume-title":"ICDMW'09","author":"Calders Toon","year":"2009","unstructured":"Toon Calders , Faisal Kamiran , and Mykola Pechenizkiy . 2009 . Building classifiers with independency constraints. In Data mining workshops, 2009 . ICDMW'09 . IEEE international conference on. IEEE, 13--18. Toon Calders, Faisal Kamiran, and Mykola Pechenizkiy. 2009. Building classifiers with independency constraints. In Data mining workshops, 2009. ICDMW'09. IEEE international conference on. IEEE, 13--18."},{"key":"e_1_3_2_1_6_1","first-page":"1","article-title":"A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions","volume":"81","author":"Chouldechova Alexandra","year":"2018","unstructured":"Alexandra Chouldechova , Emily Putnam-Hornstein , Suzanne Dworak-Peck , Diana Benavides-Prado , Oleksandr Fialko , Rhema Vaithianathan , Sorelle A Friedler , and Christo Wilson . 2018 . A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions . Proceedings of Machine Learning Research 81 (2018), 1 -- 15 . http:\/\/proceedings.mlr.press\/v81\/chouldechova18a\/chouldechova18a.pdf Alexandra Chouldechova, Emily Putnam-Hornstein, Suzanne Dworak-Peck, Diana Benavides-Prado, Oleksandr Fialko, Rhema Vaithianathan, Sorelle A Friedler, and Christo Wilson. 2018. A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions. Proceedings of Machine Learning Research 81 (2018), 1--15. http:\/\/proceedings.mlr.press\/v81\/chouldechova18a\/chouldechova18a.pdf","journal-title":"Proceedings of Machine Learning Research"},{"key":"e_1_3_2_1_7_1","volume-title":"The frontiers of fairness in machine learning. arXiv preprint arXiv:1810.08810","author":"Chouldechova Alexandra","year":"2018","unstructured":"Alexandra Chouldechova and Aaron Roth . 2018. The frontiers of fairness in machine learning. arXiv preprint arXiv:1810.08810 ( 2018 ). Alexandra Chouldechova and Aaron Roth. 2018. The frontiers of fairness in machine learning. arXiv preprint arXiv:1810.08810 (2018)."},{"key":"e_1_3_2_1_8_1","volume-title":"The measure and mismeasure of fairness: A critical review of fair machine learning. arXiv preprint arXiv:1808.00023","author":"Corbett-Davies Sam","year":"2018","unstructured":"Sam Corbett-Davies and Sharad Goel . 2018. The measure and mismeasure of fairness: A critical review of fair machine learning. arXiv preprint arXiv:1808.00023 ( 2018 ). Sam Corbett-Davies and Sharad Goel. 2018. The measure and mismeasure of fairness: A critical review of fair machine learning. arXiv preprint arXiv:1808.00023 (2018)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098095"},{"key":"e_1_3_2_1_10_1","volume-title":"The Trouble with Bias. Keynote at the Neural Information Processing Systems (NIPS) Conference","author":"Crawford Kate","year":"2017","unstructured":"Kate Crawford . 2017. The Trouble with Bias. Keynote at the Neural Information Processing Systems (NIPS) Conference ( 2017 ). https:\/\/www.youtube.com\/watch?v=fMym_BKWQzk Kate Crawford. 2017. The Trouble with Bias. Keynote at the Neural Information Processing Systems (NIPS) Conference (2017). https:\/\/www.youtube.com\/watch?v=fMym_BKWQzk"},{"key":"e_1_3_2_1_11_1","first-page":"139","article-title":"Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory and Antiracist Politics","volume":"1989","author":"Crenshaw Kimberle","year":"1989","unstructured":"Kimberle Crenshaw . 1989 . Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory and Antiracist Politics . University of Chicago Legal Forum 1989 , 1 (1989), 139 -- 167 . https:\/\/chicagounbound.uchicago.edu\/cgi\/viewcontent.cgi?article=1052&context=uclf Kimberle Crenshaw. 1989. Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory and Antiracist Politics. University of Chicago Legal Forum 1989, 1 (1989), 139--167. https:\/\/chicagounbound.uchicago.edu\/cgi\/viewcontent.cgi?article=1052&context=uclf","journal-title":"University of Chicago Legal Forum"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.aao5580"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2090236.2090255"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783311"},{"key":"e_1_3_2_1_15_1","volume-title":"Assessing and Addressing Algorithmic Bias - But Before We Get There. 2018 AAAI Spring Symposium Series Assessing (2018","author":"Garcia-Gathright Jean","year":"2018","unstructured":"Jean Garcia-Gathright , Aaron Springer , and Henriette Cramer . 2018 . Assessing and Addressing Algorithmic Bias - But Before We Get There. 2018 AAAI Spring Symposium Series Assessing (2018 ). arXiv:1809.03332 http:\/\/arxiv.org\/abs\/1809.03332 Jean Garcia-Gathright, Aaron Springer, and Henriette Cramer. 2018. Assessing and Addressing Algorithmic Bias - But Before We Get There. 2018 AAAI Spring Symposium Series Assessing (2018). arXiv:1809.03332 http:\/\/arxiv.org\/abs\/1809.03332"},{"key":"e_1_3_2_1_16_1","volume-title":"Equality of Opportunity in Supervised Learning. Advances in Neural Information Processing Systems","author":"Hardt Moritz","year":"2016","unstructured":"Moritz Hardt , Eric Price , and Nathan Srebro . 2016. Equality of Opportunity in Supervised Learning. Advances in Neural Information Processing Systems ( 2016 ), 3315--3323. arXiv:1610.02413 http:\/\/arxiv.org\/abs\/1610.02413 Moritz Hardt, Eric Price, and Nathan Srebro. 2016. Equality of Opportunity in Supervised Learning. Advances in Neural Information Processing Systems (2016), 3315--3323. arXiv:1610.02413 http:\/\/arxiv.org\/abs\/1610.02413"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1080\/1369118X.2019.1573912"},{"key":"e_1_3_2_1_18_1","volume-title":"Hal Daum\u00e9, Miro Dud\u00edk, and Hanna Wallach.","author":"Holstein Kenneth","year":"2018","unstructured":"Kenneth Holstein , Jennifer Wortman Vaughan , Hal Daum\u00e9, Miro Dud\u00edk, and Hanna Wallach. 2018 . Improving fairness in machine learning systems: What do industry practitioners need? (2018). https:\/\/doi.org\/10.1145\/3290605.3300830 arXiv:1812.05239 10.1145\/3290605.3300830 Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daum\u00e9, Miro Dud\u00edk, and Hanna Wallach. 2018. Improving fairness in machine learning systems: What do industry practitioners need? (2018). https:\/\/doi.org\/10.1145\/3290605.3300830 arXiv:1812.05239"},{"key":"e_1_3_2_1_19_1","volume-title":"Encyclopedia of Chicago","author":"Hunt D Bradford","year":"2005","unstructured":"D Bradford Hunt . 2005. Redlining. Encyclopedia of Chicago ( 2005 ). D Bradford Hunt. 2005. Redlining. Encyclopedia of Chicago (2005)."},{"key":"e_1_3_2_1_20_1","volume-title":"Gaydar: Facebook friendships expose sexual orientation. First Monday 14, 10","author":"Jernigan Carter","year":"2009","unstructured":"Carter Jernigan and Behram FT Mistree . 2009 . Gaydar: Facebook friendships expose sexual orientation. First Monday 14, 10 (2009). Carter Jernigan and Behram FT Mistree. 2009. Gaydar: Facebook friendships expose sexual orientation. First Monday 14, 10 (2009)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-011-0463-8"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33486-3_3"},{"key":"e_1_3_2_1_23_1","volume-title":"Munson","author":"Kay Matthew","year":"2015","unstructured":"Matthew Kay , Cynthia Matuszek , and Sean A . Munson . 2015 . Unequal Representation and Gender Stereotypes in Image Search Results for Occupations . (2015), 3819--3828. https:\/\/doi.org\/10.1145\/2702123.2702520 10.1145\/2702123.2702520 Matthew Kay, Cynthia Matuszek, and Sean A. Munson. 2015. Unequal Representation and Gender Stereotypes in Image Search Results for Occupations. (2015), 3819--3828. https:\/\/doi.org\/10.1145\/2702123.2702520"},{"key":"e_1_3_2_1_24_1","unstructured":"Danielle Kehl Priscilla Guo and Samuel Kessler. 2017. Algorithms in the Criminal Justice System: Assessing the Use of Risk Assessments in Sentencing. http:\/\/nrs.harvard.edu\/urn-3:HUL.InstRepos:33746041  Danielle Kehl Priscilla Guo and Samuel Kessler. 2017. Algorithms in the Criminal Justice System: Assessing the Use of Risk Assessments in Sentencing. http:\/\/nrs.harvard.edu\/urn-3:HUL.InstRepos:33746041"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.3386\/w23180"},{"key":"e_1_3_2_1_26_1","volume-title":"Inherent trade-offs in the fair determination of risk scores. Innovations in Theoretical Computer Science","author":"Kleinberg Jon","year":"2017","unstructured":"Jon Kleinberg , Sendhil Mullainathan , and Manish Raghavan . 2017. Inherent trade-offs in the fair determination of risk scores. Innovations in Theoretical Computer Science ( 2017 ). Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan. 2017. Inherent trade-offs in the fair determination of risk scores. Innovations in Theoretical Computer Science (2017)."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v028.i05"},{"key":"e_1_3_2_1_29_1","volume-title":"com: A versatile crowdsourcing data acquisition platform for the behavioral sciences. Behavior research methods 49, 2","author":"Litman Leib","year":"2017","unstructured":"Leib Litman , Jonathan Robinson , and Tzvi Abberbock . 2017. TurkPrime. com: A versatile crowdsourcing data acquisition platform for the behavioral sciences. Behavior research methods 49, 2 ( 2017 ), 433--442. Leib Litman, Jonathan Robinson, and Tzvi Abberbock. 2017. TurkPrime. com: A versatile crowdsourcing data acquisition platform for the behavioral sciences. Behavior research methods 49, 2 (2017), 433--442."},{"volume-title":"The American Stratification System","author":"Massey Douglass S.","key":"e_1_3_2_1_30_1","unstructured":"Douglass S. Massey . 2007. Categorically Unequal . The American Stratification System . Russell Sage Foundation , New York . Douglass S. Massey. 2007. Categorically Unequal. The American Stratification System. Russell Sage Foundation, New York."},{"key":"e_1_3_2_1_31_1","volume-title":"Prediction-based decisions and fairness: A catalogue of choices, assumptions, and definitions. arXiv preprint arXiv:1811.07867","author":"Mitchell Shira","year":"2018","unstructured":"Shira Mitchell , Eric Potash , and Solon Barocas . 2018. Prediction-based decisions and fairness: A catalogue of choices, assumptions, and definitions. arXiv preprint arXiv:1811.07867 ( 2018 ). Shira Mitchell, Eric Potash, and Solon Barocas. 2018. Prediction-based decisions and fairness: A catalogue of choices, assumptions, and definitions. arXiv preprint arXiv:1811.07867 (2018)."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1111\/j.1740-9713.2017.01012.x","article-title":"Fairness and transparency in the age of the algorithm","volume":"14","author":"Olhede Sofia","year":"2017","unstructured":"Sofia Olhede and Russell Rodrigues . 2017 . Fairness and transparency in the age of the algorithm . Significance 14 , 2 (2017), 8 -- 9 . https:\/\/doi.org\/10.1111\/j.1740-9713.2017.01012.x arXiv:1609.05807 10.1111\/j.1740-9713.2017.01012.x Sofia Olhede and Russell Rodrigues. 2017. Fairness and transparency in the age of the algorithm. Significance 14, 2 (2017), 8--9. https:\/\/doi.org\/10.1111\/j.1740-9713.2017.01012.x arXiv:1609.05807","journal-title":"Significance"},{"volume-title":"Weapons of Math Destruction. How Big Data Increases Inequality and Threatens Democracy. Crown\/Archetype","author":"O'Neill Cathy","key":"e_1_3_2_1_33_1","unstructured":"Cathy O'Neill . 2016. Weapons of Math Destruction. How Big Data Increases Inequality and Threatens Democracy. Crown\/Archetype , New York . Cathy O'Neill. 2016. Weapons of Math Destruction. How Big Data Increases Inequality and Threatens Democracy. Crown\/Archetype, New York."},{"key":"e_1_3_2_1_34_1","first-page":"2","article-title":"Mass Imprisonment and the Life Course: Race and Class Inequality in U.","volume":"69","author":"Pettit Becky","year":"2004","unstructured":"Becky Pettit and Bruce Western . 2004 . Mass Imprisonment and the Life Course: Race and Class Inequality in U. S. Incarceration. American Sociological Review 69 , 2 (apr 2004), 151--169. https:\/\/doi.org\/10.1177\/000312240406900201 10.1177\/000312240406900201 Becky Pettit and Bruce Western. 2004. Mass Imprisonment and the Life Course: Race and Class Inequality in U.S. Incarceration. American Sociological Review 69, 2 (apr 2004), 151--169. https:\/\/doi.org\/10.1177\/000312240406900201","journal-title":"S. Incarceration. American Sociological Review"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/2460276.2460278"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"crossref","unstructured":"Charles Tilly. 1999. Durable Inequality. University of California Press.  Charles Tilly. 1999. Durable Inequality. University of California Press.","DOI":"10.1525\/9780520924222"},{"key":"e_1_3_2_1_37_1","volume-title":"Max Van Kleek, and Reuben Binns","author":"Veale Michael","year":"2018","unstructured":"Michael Veale , Max Van Kleek, and Reuben Binns . 2018 . Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making . (2018). https:\/\/doi.org\/10.1145\/3173574.3174014 arXiv:1802.01029 10.1145\/3173574.3174014 Michael Veale, Max Van Kleek, and Reuben Binns. 2018. Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making. (2018). https:\/\/doi.org\/10.1145\/3173574.3174014 arXiv:1802.01029"},{"key":"e_1_3_2_1_38_1","volume-title":"Learning non-discriminatory predictors. Preprint arXiv:1702.06081","author":"Woodworth Blake","year":"2017","unstructured":"Blake Woodworth , Suriya Gunasekar , Mesrob I Ohannessian , and Nathan Srebro . 2017. Learning non-discriminatory predictors. Preprint arXiv:1702.06081 ( 2017 ). Blake Woodworth, Suriya Gunasekar, Mesrob I Ohannessian, and Nathan Srebro. 2017. Learning non-discriminatory predictors. Preprint arXiv:1702.06081 (2017)."},{"key":"e_1_3_2_1_39_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 . Fairness constraints: Mechanisms for fair classification. In Artificial Intelligence and Statistics . 962--970. Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, and Krishna P Gummadi. 2017. Fairness constraints: Mechanisms for fair classification. In Artificial Intelligence and Statistics. 962--970."},{"key":"e_1_3_2_1_40_1","volume-title":"Proceedings of the 30th International Conference on Machine Learning (ICML-13)","author":"Zemel Rich","year":"2013","unstructured":"Rich Zemel , Yu Wu , Kevin Swersky , Toni Pitassi , and Cynthia Dwork . 2013 . Learning fair representations . In Proceedings of the 30th International Conference on Machine Learning (ICML-13) . 325--333. Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, and Cynthia Dwork. 2013. Learning fair representations. In Proceedings of the 30th International Conference on Machine Learning (ICML-13). 325--333."},{"key":"e_1_3_2_1_41_1","volume-title":"Identifying significant predictive bias in classifiers. arXiv preprint arXiv:1611.08292","author":"Zhang Zhe","year":"2016","unstructured":"Zhe Zhang and Daniel B Neill . 2016. Identifying significant predictive bias in classifiers. arXiv preprint arXiv:1611.08292 ( 2016 ). Zhe Zhang and Daniel B Neill. 2016. Identifying significant predictive bias in classifiers. arXiv preprint arXiv:1611.08292 (2016)."}],"event":{"name":"COMPASS '20: ACM SIGCAS Conference on Computing and Sustainable Societies","sponsor":["SIGCAS ACM Special Interest Group on Computers and Society"],"location":"Ecuador","acronym":"COMPASS '20"},"container-title":["Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3378393.3402507","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3378393.3402507","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:45:03Z","timestamp":1750203903000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3378393.3402507"}},"subtitle":["A Comparison of Human and Machine Recidivism Risk Predictions"],"short-title":[],"issued":{"date-parts":[[2020,6,15]]},"references-count":40,"alternative-id":["10.1145\/3378393.3402507","10.1145\/3378393"],"URL":"https:\/\/doi.org\/10.1145\/3378393.3402507","relation":{},"subject":[],"published":{"date-parts":[[2020,6,15]]},"assertion":[{"value":"2020-07-01","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}