{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T01:29:31Z","timestamp":1768008571418,"version":"3.49.0"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2017,5,18]],"date-time":"2017-05-18T00:00:00Z","timestamp":1495065600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2017,5,18]],"date-time":"2017-05-18T00:00:00Z","timestamp":1495065600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/100000145","name":"Division of Information and Intelligent Systems","doi-asserted-by":"publisher","award":["1646654"],"award-info":[{"award-number":["1646654"]}],"id":[{"id":"10.13039\/100000145","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Data Sci Anal"],"published-print":{"date-parts":[[2017,8]]},"DOI":"10.1007\/s41060-017-0058-x","type":"journal-article","created":{"date-parts":[[2017,5,18]],"date-time":"2017-05-18T16:51:35Z","timestamp":1495126295000},"page":"1-16","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Anti-discrimination learning: a causal modeling-based framework"],"prefix":"10.1007","volume":"4","author":[{"given":"Lu","family":"Zhang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2823-3063","authenticated-orcid":false,"given":"Xintao","family":"Wu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,5,18]]},"reference":[{"key":"58_CR1","unstructured":"Adler, P., Falk, C., Friedler, S.A., Rybeck, G., Scheidegger, C., Smith, B., Venkatasubramanian, S.: Auditing black-box models for indirect influence. In: Data Mining (ICDM), 2016 IEEE 16th International Conference on, pp. 1\u201310. IEEE, (2016)"},{"key":"58_CR2","unstructured":"Avin, C., Shpitser, I., Pearl, J.: Identifiability of path-specific effects. In: IJCAI\u201905, pp. 357\u2013363. (2005)"},{"key":"58_CR3","unstructured":"Barocas, S., Selbst, A.D.: Big data\u2019s disparate impact. Calif. Law Rev. 104(3), 671\u2013769 (2016)"},{"issue":"1","key":"58_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s41060-016-0040-z","volume":"3","author":"F Bonchi","year":"2017","unstructured":"Bonchi, F., Hajian, S., Mishra, B., Ramazzotti, D.: Exposing the probabilistic causal structure of discrimination. Int. J. Data Sci. Anal. 3(1), 1\u201321 (2017)","journal-title":"Int. J. Data Sci. Anal."},{"issue":"4175","key":"58_CR5","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1126\/science.187.4175.398","volume":"187","author":"PJ Bickel","year":"1975","unstructured":"Bickel, P.J., Hammel, E.A., OConnell, J.W.: Sex bias in graduate admissions: data from Berkeley. Science 187(4175), 398\u2013404 (1975)","journal-title":"Science"},{"key":"58_CR6","unstructured":"Podesta, J., Pritzker, P., Moniz, E.J., Holdren, J., Zients, J.: Big data: seizing opportunities, preserving values. Executive Office of the President (2014)"},{"issue":"2","key":"58_CR7","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1007\/s10618-010-0190-x","volume":"21","author":"T Calders","year":"2010","unstructured":"Calders, T., Verwer, S.: Three naive bayes approaches for discrimination-free classification. Data Min. Knowl. Discov. 21(2), 277\u2013292 (2010)","journal-title":"Data Min. Knowl. Discov."},{"issue":"1","key":"58_CR8","first-page":"3741","volume":"15","author":"D Colombo","year":"2014","unstructured":"Colombo, D., Maathuis, M.H.: Order-independent constraint-based causal structure learning. JMLR 15(1), 3741\u20133782 (2014)","journal-title":"JMLR"},{"key":"58_CR9","doi-asserted-by":"crossref","unstructured":"Dwork, C., Hardt, M., Pitassi, T., Reingold, O., Zemel, R.: Fairness through awareness. In: Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, pp. 214\u2013226. ACM, (2012)","DOI":"10.1145\/2090236.2090255"},{"issue":"2","key":"58_CR10","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/s41060-016-0038-6","volume":"3","author":"F Eberhardt","year":"2017","unstructured":"Eberhardt, F.: Introduction to the foundations of causal discovery. Int. J. Data Sci. Anal. 3(2), 81\u201391 (2017)","journal-title":"Int. J. Data Sci. Anal."},{"issue":"4","key":"58_CR11","doi-asserted-by":"publisher","first-page":"1452","DOI":"10.1214\/14-AOS1206","volume":"42","author":"RJ Evans","year":"2014","unstructured":"Evans, R.J., Richardson, T.S., et al.: Markovian acyclic directed mixed graphs for discrete data. Ann. Stat. 42(4), 1452\u20131482 (2014)","journal-title":"Ann. Stat."},{"key":"58_CR12","doi-asserted-by":"crossref","unstructured":"Feldman, M., Friedler, S.A., Moeller, J., Scheidegger, C., Venkatasubramanian, S.: Certifying and removing disparate impact. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 259\u2013268. ACM, (2015)","DOI":"10.1145\/2783258.2783311"},{"issue":"7","key":"58_CR13","doi-asserted-by":"publisher","first-page":"1445","DOI":"10.1109\/TKDE.2012.72","volume":"25","author":"S Hajian","year":"2013","unstructured":"Hajian, S., Domingo-Ferrer, J.: A methodology for direct and indirect discrimination prevention in data mining. IEEE Trans. Knowl. Data Eng. 25(7), 1445\u20131459 (2013)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"6","key":"58_CR14","doi-asserted-by":"publisher","first-page":"1733","DOI":"10.1007\/s10618-014-0393-7","volume":"29","author":"S Hajian","year":"2015","unstructured":"Hajian, S., Domingo-Ferrer, J., Monreale, A., Pedreschi, D., Giannotti, F.: Discrimination-and privacy-aware patterns. Data Min. Knowl. Discov. 29(6), 1733\u20131782 (2015)","journal-title":"Data Min. Knowl. Discov."},{"key":"58_CR15","unstructured":"Hardt, M., Price, E., Srebro, N.: Equality of opportunity in supervised learning. In: Advances in Neural Information Processing Systems (NIPS), pp. 3315\u20133323 (2016)"},{"key":"58_CR16","first-page":"613","volume":"8","author":"M Kalisch","year":"2007","unstructured":"Kalisch, M., B\u00fchlmann, P.: Estimating high-dimensional directed acyclic graphs with the pc-algorithm. J. Mach. Learn. Res. 8, 613\u2013636 (2007)","journal-title":"J. Mach. Learn. Res."},{"issue":"1","key":"58_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10115-011-0463-8","volume":"33","author":"F Kamiran","year":"2012","unstructured":"Kamiran, F., Calders, T.: Data preprocessing techniques for classification without discrimination. Knowl. Inf. Syst. 33(1), 1\u201333 (2012)","journal-title":"Knowl. Inf. Syst."},{"key":"58_CR18","doi-asserted-by":"crossref","unstructured":"Kamiran, F., Calders, T., Pechenizkiy, M.: Discrimination aware decision tree learning. In: 2010 IEEE 10th International Conference on Data Mining (ICDM), pp. 869\u2013874. IEEE, (2010)","DOI":"10.1109\/ICDM.2010.50"},{"key":"58_CR19","doi-asserted-by":"crossref","unstructured":"Kamishima, T., Akaho, S., Sakuma, J.: Fairness-aware learning through regularization approach. In: 2011 IEEE 11th International Conference on Data Mining Workshops (ICDMW), pp. 643\u2013650. IEEE, (2011)","DOI":"10.1109\/ICDMW.2011.83"},{"key":"58_CR20","doi-asserted-by":"crossref","unstructured":"Luong, B.T., Ruggieri, S., Turini, F.: k-NN as an implementation of situation testing for discrimination discovery and prevention. In: Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 502\u2013510. ACM, (2011)","DOI":"10.1145\/2020408.2020488"},{"issue":"2","key":"58_CR21","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s10506-014-9156-4","volume":"22","author":"K Mancuhan","year":"2014","unstructured":"Mancuhan, K., Clifton, C.: Combating discrimination using bayesian networks. Artif. Intell. Law 22(2), 211\u2013238 (2014)","journal-title":"Artif. Intell. Law"},{"key":"58_CR22","unstructured":"Munoz, C., Smith, M., Patil, D.: Big data: a report on algorithmic systems, opportunity, and civil rights. Executive Office of the President (2016)"},{"key":"58_CR23","volume-title":"Learning Bayesian Networks","author":"RE Neapolitan","year":"2004","unstructured":"Neapolitan, R.E., et al.: Learning Bayesian Networks, vol. 38. Prentice Hall, Upper Saddle River (2004)"},{"key":"58_CR24","unstructured":"Pearl, J.: Causality. Cambridge University Press, Cambridge (2009)"},{"key":"58_CR25","unstructured":"Pearl, J.: The do-calculus revisited. In: Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, pp. 3\u201311. AUAI Press, (2012)"},{"key":"58_CR26","doi-asserted-by":"crossref","unstructured":"Pedreschi, D., Ruggieri, S., Turini, F.: Measuring discrimination in socially-sensitive decision records. In: Proceedings of the 2009 SIAM International Conference on Data Mining, pp. 581\u2013592. SIAM, (2009)","DOI":"10.1137\/1.9781611972795.50"},{"key":"58_CR27","doi-asserted-by":"crossref","unstructured":"Pedreshi, D., Ruggieri, S., Turini, F.: Discrimination-aware data mining. In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 560\u2013568. ACM, (2008)","DOI":"10.1145\/1401890.1401959"},{"key":"58_CR28","unstructured":"Qureshi, B., Kamiran, F., Karim, A., Ruggieri, S.: Causal discrimination discovery through propensity score analysis. arXiv preprint arXiv:1608.03735 (2016)"},{"issue":"05","key":"58_CR29","doi-asserted-by":"publisher","first-page":"582","DOI":"10.1017\/S0269888913000039","volume":"29","author":"A Romei","year":"2014","unstructured":"Romei, A., Ruggieri, S.: A multidisciplinary survey on discrimination analysis. Knowl. Eng. Rev. 29(05), 582\u2013638 (2014)","journal-title":"Knowl. Eng. Rev."},{"issue":"2","key":"58_CR30","first-page":"9","volume":"4","author":"S Ruggieri","year":"2010","unstructured":"Ruggieri, S., Pedreschi, D., Turini, F.: Data mining for discrimination discovery. ACM Trans. Knowl. Discov. Data (TKDD) 4(2), 9 (2010)","journal-title":"ACM Trans. Knowl. Discov. Data (TKDD)"},{"issue":"6","key":"58_CR31","doi-asserted-by":"publisher","first-page":"1011","DOI":"10.1111\/cogs.12058","volume":"37","author":"I Shpitser","year":"2013","unstructured":"Shpitser, I.: Counterfactual graphical models for longitudinal mediation analysis with unobserved confounding. Cogn. Sci. 37(6), 1011\u20131035 (2013)","journal-title":"Cogn. Sci."},{"issue":"1","key":"58_CR32","doi-asserted-by":"publisher","first-page":"3","DOI":"10.2333\/bhmk.41.3","volume":"41","author":"I Shpitser","year":"2014","unstructured":"Shpitser, I., Evans, R.J., Richardson, T.S., Robins, J.M.: Introduction to nested Markov models. Behaviormetrika 41(1), 3\u201339 (2014)","journal-title":"Behaviormetrika"},{"key":"58_CR33","volume-title":"Causation, Prediction, and Search","author":"P Spirtes","year":"2000","unstructured":"Spirtes, P., Glymour, C.N., Scheines, R.: Causation, Prediction, and Search, vol. 81. MIT press, Cambridge (2000)"},{"issue":"1\u20134","key":"58_CR34","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1023\/A:1018912507879","volume":"28","author":"J Tian","year":"2000","unstructured":"Tian, J., Pearl, J.: Probabilities of causation: bounds and identification. Ann. Math. Artif. Intell. 28(1\u20134), 287\u2013313 (2000)","journal-title":"Ann. Math. Artif. Intell."},{"key":"58_CR35","doi-asserted-by":"crossref","unstructured":"Wu, Y., Wu, X.: Using loglinear model for discrimination discovery and prevention. In: 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), pp. 110\u2013119. IEEE, (2016)","DOI":"10.1109\/DSAA.2016.18"},{"key":"58_CR36","doi-asserted-by":"crossref","unstructured":"Yang, K., Stoyanovich, J.: Measuring fairness in ranked outputs. In: FATML. (2016)","DOI":"10.1145\/3085504.3085526"},{"key":"58_CR37","first-page":"325","volume":"28","author":"RS Zemel","year":"2013","unstructured":"Zemel, R.S., Wu, Y., Swersky, K., Pitassi, T., Dwork, C.: Learning fair representations. ICML 28, 325\u2013333 (2013)","journal-title":"ICML"},{"key":"58_CR38","doi-asserted-by":"crossref","unstructured":"Zhang, L., Wu, Y., Wu, X.: Achieving non-discrimination in data release. arXiv preprint arXiv:1611.07438 (2016)","DOI":"10.1145\/3097983.3098167"},{"key":"58_CR39","doi-asserted-by":"crossref","unstructured":"Zhang, L., Wu, Y., Wu, X.: On discrimination discovery using causal networks. In: Proceedings of SBP-BRiMS 2016. (2016)","DOI":"10.1007\/978-3-319-39931-7_9"},{"key":"58_CR40","doi-asserted-by":"crossref","unstructured":"Zhang, L., Wu, Y., Wu, X.: Situation testing-based discrimination discovery: a causal inference approach. In: Proceedings of IJCAI\u201916 (2016)","DOI":"10.1007\/978-3-319-39931-7_9"},{"key":"58_CR41","doi-asserted-by":"crossref","unstructured":"Zhang, L., Wu, Y., Wu, X.: Achieving non-discrimination in prediction. arXiv preprint arXiv:1703.00060 (2017)","DOI":"10.24963\/ijcai.2018\/430"},{"key":"58_CR42","doi-asserted-by":"crossref","unstructured":"Zhang, L., Wu, Y., Wu, X.: A causal framework for discovering and removing direct and indirect discrimination. In: Proceedings of IJCAI\u201917 (2017)","DOI":"10.24963\/ijcai.2017\/549"},{"key":"58_CR43","doi-asserted-by":"crossref","unstructured":"\u017dliobaite, I., Kamiran, F., Calders, T.: Handling conditional discrimination. In: 2011 IEEE 11th International Conference on Data Mining (ICDM), pp. 992\u20131001. IEEE, (2011)","DOI":"10.1109\/ICDM.2011.72"}],"container-title":["International Journal of Data Science and Analytics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s41060-017-0058-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s41060-017-0058-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s41060-017-0058-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,28]],"date-time":"2022-07-28T18:21:15Z","timestamp":1659032475000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s41060-017-0058-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,18]]},"references-count":43,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,8]]}},"alternative-id":["58"],"URL":"https:\/\/doi.org\/10.1007\/s41060-017-0058-x","relation":{},"ISSN":["2364-415X","2364-4168"],"issn-type":[{"value":"2364-415X","type":"print"},{"value":"2364-4168","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,5,18]]},"assertion":[{"value":"12 April 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 May 2017","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 May 2017","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"On behalf of all authors, the corresponding author states that there is no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}