{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T02:07:56Z","timestamp":1743041276535,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031637346"},{"type":"electronic","value":"9783031637353"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-63735-3_10","type":"book-chapter","created":{"date-parts":[[2024,7,22]],"date-time":"2024-07-22T21:02:07Z","timestamp":1721682127000},"page":"165-181","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["New Proportion Measures of\u00a0Discrimination Based on\u00a0Natural Direct and\u00a0Indirect Effects"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4135-8741","authenticated-orcid":false,"given":"Ryusei","family":"Shingaki","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4219-351X","authenticated-orcid":false,"given":"Manabu","family":"Kuroki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,23]]},"reference":[{"issue":"439","key":"10_CR1","doi-asserted-by":"publisher","first-page":"1171","DOI":"10.1080\/01621459.1997.10474074","volume":"92","author":"A Balke","year":"1997","unstructured":"Balke, A., Pearl, J.: Bounds on treatment effects from studies with imperfect compliance. J. Amer. Statist. Assoc. 92(439), 1171\u20131176 (1997)","journal-title":"J. Amer. Statist. Assoc."},{"key":"10_CR2","doi-asserted-by":"publisher","unstructured":"Becker, B., Kohavi, R.: Adult. UCI Machine Learning Repository (1996). https:\/\/doi.org\/10.24432\/C5XW20","DOI":"10.24432\/C5XW20"},{"issue":"3","key":"10_CR3","doi-asserted-by":"publisher","first-page":"695","DOI":"10.1111\/j.1541-0420.2007.00949.x","volume":"64","author":"Z Cai","year":"2008","unstructured":"Cai, Z., Kuroki, M., Pearl, J., Tian, J.: Bounds on direct effects in the presence of confounded intermediate variables. Biometrics 64(3), 695\u2013701 (2008)","journal-title":"Biometrics"},{"key":"10_CR4","unstructured":"Hamilton, E.: Benchmarking four approaches to fairness-aware machine learning. Ph.D. thesis, Haverford College. Department of Computer Science (2017). https:\/\/scholarship.tricolib.brynmawr.edu\/handle\/10066\/19295"},{"issue":"6","key":"10_CR5","doi-asserted-by":"publisher","first-page":"920","DOI":"10.1002\/jae.2341","volume":"29","author":"M Huber","year":"2014","unstructured":"Huber, M.: Identifying causal mechanisms (primarily) based on inverse probability weighting. J. Appl. Economet. 29(6), 920\u2013943 (2014)","journal-title":"J. Appl. Economet."},{"issue":"4","key":"10_CR6","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1017\/S0003055411000414","volume":"105","author":"K Imai","year":"2011","unstructured":"Imai, K., Keele, L., Tingley, D., Yamamoto, T.: Unpacking the black box of causality: learning about causal mechanisms from experimental and observational studies. Am. Polit. Sci. Rev. 105(4), 765\u2013789 (2011)","journal-title":"Am. Polit. Sci. Rev."},{"key":"10_CR7","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1007\/978-3-642-33486-3_3","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"T Kamishima","year":"2012","unstructured":"Kamishima, T., Akaho, S., Asoh, H., Sakuma, J.: Fairness-aware classifier with prejudice remover regularizer. In: Flach, P.A., De Bie, T., Cristianini, N. (eds.) ECML PKDD 2012. LNCS (LNAI), vol. 7524, pp. 35\u201350. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33486-3_3"},{"key":"10_CR8","unstructured":"Kilbertus, N., Rojas-Carulla, M., Parascandolo, G., Hardt, M., Janzing, D., Sch\u00f6lkopf, B.: Avoiding discrimination through causal reasoning. In: Proceedings of the 31st International Conference on Neural Information Processing Systems, NIPS 2017, pp. 656\u2013666. Curran Associates Inc., Red Hook (2017)"},{"key":"10_CR9","unstructured":"Kusner, M.J., Loftus, J., Russell, C., Silva, R.: Counterfactual fairness. In: Guyon, I., et al. (eds.) Advances in Neural Information Processing Systems, NIPS 2017, vol. 30, pp. 4066\u20134076. Curran Associates, Inc. (2017)"},{"key":"10_CR10","doi-asserted-by":"crossref","unstructured":"Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, Burlington (1988)","DOI":"10.1016\/B978-0-08-051489-5.50008-4"},{"key":"10_CR11","unstructured":"Pearl, J.: Direct and indirect effects. In: Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence, pp. 411\u2013420. Morgan Kaufmann Publishers Inc., San Francisco (2001)"},{"key":"10_CR12","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511803161","volume-title":"Causality: Models, Reasoning and Inference","author":"J Pearl","year":"2009","unstructured":"Pearl, J.: Causality: Models, Reasoning and Inference, 2nd edn. Cambridge University Press, Cambridge (2009)","edition":"2"},{"issue":"3","key":"10_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3494672","volume":"55","author":"D Pessach","year":"2022","unstructured":"Pessach, D., Shmueli, E.: A review on fairness in machine learning. ACM Comput. Surv. 55(3), 1\u201344 (2022)","journal-title":"ACM Comput. Surv."},{"key":"10_CR14","unstructured":"Plecko, D., Bareinboim, E.: Causal fairness analysis. Technical report, R-90, Causal Artificial Intelligence Lab, Columbia University (2022)"},{"issue":"4","key":"10_CR15","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1002\/sim.4780080407","volume":"8","author":"RL Prentice","year":"1989","unstructured":"Prentice, R.L.: Surrogate endpoints in clinical trials: definition and operational criteria. Stat. Med. 8(4), 431\u2013440 (1989)","journal-title":"Stat. Med."},{"key":"10_CR16","doi-asserted-by":"crossref","unstructured":"Toreini, E., Aitken, M., Coopamootoo, K., Elliott, K., Zelaya, C.G., van Moorsel, A.: The relationship between trust in AI and trustworthy machine learning technologies. In: Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, FAT* 2020, pp. 272\u2013283. Association for Computing Machinery, New York (2020)","DOI":"10.1145\/3351095.3372834"},{"issue":"4","key":"10_CR17","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1111\/j.0006-341X.2002.00803.x","volume":"58","author":"Y Wang","year":"2002","unstructured":"Wang, Y., Taylor, J.M.G.: A measure of the proportion of treatment effect explained by a surrogate marker. Biometrics 58(4), 803\u2013812 (2002)","journal-title":"Biometrics"},{"key":"10_CR18","doi-asserted-by":"crossref","unstructured":"Zafar, M.B., Valera, I., Gomez\u00a0Rodriguez, M., Gummadi, K.P.: Fairness beyond disparate treatment & disparate impact: learning classification without disparate mistreatment. In: Proceedings of the 26th International Conference on World Wide Web, WWW 2017, pp. 1171\u20131180. International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE (2017)","DOI":"10.1145\/3038912.3052660"},{"key":"10_CR19","doi-asserted-by":"crossref","unstructured":"Zhang, J., Bareinboim, E.: Fairness in decision-making - the causal explanation formula. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 32, no. 1 (2018)","DOI":"10.1609\/aaai.v32i1.11564"},{"key":"10_CR20","doi-asserted-by":"publisher","first-page":"1060","DOI":"10.1007\/s10618-017-0506-1","volume":"31","author":"I \u017dliobait\u0117","year":"2017","unstructured":"\u017dliobait\u0117, I.: Measuring discrimination in algorithmic decision making. Data Min. Knowl. Disc. 31, 1060\u20131089 (2017)","journal-title":"Data Min. Knowl. Disc."}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence and Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-63735-3_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,22]],"date-time":"2024-07-22T21:04:28Z","timestamp":1721682268000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-63735-3_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031637346","9783031637353"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-63735-3_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"23 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"This research was funded by JFE Engineering Corporation and Japan Society for the Promotion of Science (JSPS), Grant Number 19K11856 and 21H03504.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"ISAIM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Artificial Intelligence and Mathematics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Fort Lauderdale, FL","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 January 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 January 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isaim2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/isaim2024.cs.ou.edu\/iwcia.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}