{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T19:09:14Z","timestamp":1768417754017,"version":"3.49.0"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031116469","type":"print"},{"value":"9783031116476","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-11647-6_1","type":"book-chapter","created":{"date-parts":[[2022,7,25]],"date-time":"2022-07-25T12:04:01Z","timestamp":1658750641000},"page":"3-9","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["The Black-Box Syndrome: Embracing Randomness in Machine Learning Models"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5359-4111","authenticated-orcid":false,"given":"Z.","family":"Anthis","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,26]]},"reference":[{"issue":"1","key":"1_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s41239-018-0109-y","volume":"15","author":"L Casta\u00f1eda","year":"2018","unstructured":"Casta\u00f1eda, L., Selwyn, N.: More than tools? Making sense of the ongoing digitizations of higher education. Int. J. Educ. Technol. High. Educ. 15(1), 1 (2018). https:\/\/doi.org\/10.1186\/s41239-018-0109-y","journal-title":"Int. J. Educ. Technol. High. Educ."},{"key":"1_CR2","unstructured":"Pedro, F., et al.:\u00a0Artificial intelligence in education: challenges and opportunities for sustainable development\u00a0(2019)"},{"issue":"1","key":"1_CR3","first-page":"1","volume":"11","author":"RS Baker","year":"2019","unstructured":"Baker, R.S.: Challenges for the future of educational data mining: the Baker learning analytics prizes. JEDM J. Edu. Data Min. 11(1), 1\u201317 (2019)","journal-title":"JEDM J. Edu. Data Min."},{"key":"1_CR4","first-page":"49","volume":"17","author":"Z Papamitsiou","year":"2014","unstructured":"Papamitsiou, Z., Economides, A.: Learning analytics and educational data mining in practice: a systematic literature review of empirical evidence. Educ. Technol. Soc. 17, 49\u201364 (2014)","journal-title":"Educ. Technol. Soc."},{"issue":"3","key":"1_CR5","first-page":"50","volume":"38","author":"B Goodman","year":"2017","unstructured":"Goodman, B., Flaxman, S.: European union regulations on algorithmic decision-making and a \u201cright to explanation.\u201d AI Mag. 38(3), 50\u201357 (2017)","journal-title":"AI Mag."},{"key":"1_CR6","unstructured":"Ashoori, M.,\u00a0 Weisz,\u00a0J.D.:\u00a0In AI we trust? Factors that influence trustworthiness of AI-infused decision-making processes. arXiv preprint arXiv:1912.02675\u00a0(2019)"},{"key":"1_CR7","doi-asserted-by":"crossref","unstructured":"Toreini, E., et al.:\u00a0The relationship between trust in AI and trustworthy machine learning technologies.\u00a0In:\u00a0Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, Barcelona, Spain, pp. 272\u2013283.\u00a0Association for Computing Machinery (2020)","DOI":"10.1145\/3351095.3372834"},{"key":"1_CR8","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: \u201cWhy should I trust you?\u201d Explaining the predictions of any classifier. In:\u00a0Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining\u00a0(2016)","DOI":"10.1145\/2939672.2939778"},{"key":"1_CR9","unstructured":"Gunning, D.:\u00a0Explainable artificial intelligence (xai). Defense Advanced Research Projects Agency (DARPA), nd Web,\u00a02(2)\u00a0(2017)"},{"issue":"8","key":"1_CR10","doi-asserted-by":"publisher","first-page":"832","DOI":"10.3390\/electronics8080832","volume":"8","author":"DV Carvalho","year":"2019","unstructured":"Carvalho, D.V., Pereira, E.M., Cardoso, J.S.: Machine learning interpretability: a survey on methods and metrics. Electronics 8(8), 832 (2019)","journal-title":"Electronics"},{"key":"1_CR11","unstructured":"Doshi-Velez, F., Kim, B.:\u00a0Towards a rigorous science of interpretable machine learning. arXiv preprint arXiv:1702.08608\u00a0(2017)"},{"key":"1_CR12","doi-asserted-by":"crossref","unstructured":"Lou, Y., Caruana, R., Gehrke, J.:\u00a0Intelligible models for classification and regression. In:\u00a0Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining\u00a0(2012)","DOI":"10.1145\/2339530.2339556"},{"key":"1_CR13","unstructured":"Eban, E., et al.:\u00a0Scalable learning of non-decomposable objectives. In:\u00a0Proceedings of the 20th International Conference on Artificial Intelligence and Statistics. PMLR (2017)"},{"issue":"6","key":"1_CR14","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1007\/s10207-012-0177-2","volume":"11","author":"D Bogdanov","year":"2012","unstructured":"Bogdanov, D., et al.: High-performance secure multi-party computation for data mining applications. Int. J. Inf. Secur. 11(6), 403\u2013418 (2012)","journal-title":"Int. J. Inf. Secur."},{"key":"1_CR15","unstructured":"Papenmeier, A., Englebienne, G., Seifert, C.:\u00a0How model accuracy and explanation fidelity influence user trust. arXiv preprint arXiv:1907.12652\u00a0(2019)"},{"key":"1_CR16","doi-asserted-by":"crossref","unstructured":"Vandekerckhove, J., Matzke, D., Wagenmakers,\u00a0E.-J.:\u00a0Model comparison and the principle of parsimony. In:\u00a0Busemeyer,\u00a0 J.R., Wang, Z., Townsend,\u00a0 J.T., Eidels, A. (eds.)\u00a0Oxford Handbook of Computational and Mathematical Psychology, pp. 300\u2013319. Oxford University Press, Oxford (2015)","DOI":"10.1093\/oxfordhb\/9780199957996.013.14"},{"key":"1_CR17","unstructured":"Herman, B.:\u00a0The promise and peril of human evaluation for model interpretability, p. 8. arXiv preprint arXiv:1711.07414\u00a0(2017)"},{"key":"1_CR18","doi-asserted-by":"crossref","unstructured":"Do\u0161ilovi\u0107, F.K., Br\u010di\u0107, M., Hlupi\u0107, N.:\u00a0Explainable artificial intelligence: a survey. In:\u00a02018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). IEEE\u00a0(2018)","DOI":"10.23919\/MIPRO.2018.8400040"},{"key":"1_CR19","doi-asserted-by":"crossref","unstructured":"Abdul, A., et al.:\u00a0Trends and trajectories for explainable, accountable and intelligible systems: an HCI research agenda.\u00a0In:\u00a0Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems,\u00a0Montreal QC, Canada,\u00a0p. 582. Association for Computing Machinery (2018)","DOI":"10.1145\/3173574.3174156"},{"key":"1_CR20","series-title":"Advances in Mathematics Education","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1007\/978-94-007-7155-0_2","volume-title":"Probabilistic Thinking","author":"M Borovcnik","year":"2014","unstructured":"Borovcnik, M., Kapadia, R.: A historical and philosophical perspective on probability. In: Chernoff, E.J., Sriraman, B. (eds.) Probabilistic Thinking. AME, pp. 7\u201334. Springer, Dordrecht (2014). https:\/\/doi.org\/10.1007\/978-94-007-7155-0_2"},{"key":"1_CR21","unstructured":"Batanero, C.:\u00a0Understanding randomness: challenges for research and teaching. In:\u00a0CERME 9-Ninth Congress of the European Society for Research in Mathematics Education\u00a0(2015)"},{"key":"1_CR22","volume-title":"Conformal prediction for reliable machine learning: theory, adaptations and applications","author":"V Balasubramanian","year":"2014","unstructured":"Balasubramanian, V., Ho, S.-S., Vovk, V.: Conformal Prediction for Reliable Machine Learning: Theory, Adaptations and Applications. Newnes, London (2014)"},{"key":"1_CR23","volume-title":"Probability and computing: Randomization and probabilistic techniques in algorithms and data analysis","author":"M Mitzenmacher","year":"2017","unstructured":"Mitzenmacher, M., Upfal, E.: Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis. Cambridge University Press, Cambridge (2017)"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners\u2019 and Doctoral Consortium"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-11647-6_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T16:16:40Z","timestamp":1710260200000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-11647-6_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031116469","9783031116476"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-11647-6_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"26 July 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIED","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Intelligence in Education","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Durham","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 July 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 July 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aied2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aied2022.webspace.durham.ac.uk\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"243","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"40","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"40","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"16% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}