{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T05:25:31Z","timestamp":1773552331501,"version":"3.50.1"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T00:00:00Z","timestamp":1682035200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T00:00:00Z","timestamp":1682035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100000155","name":"Social Sciences and Humanities Research Council of Canada","doi-asserted-by":"publisher","award":["752-2022-1772"],"award-info":[{"award-number":["752-2022-1772"]}],"id":[{"id":"10.13039\/501100000155","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008240","name":"Fonds de Recherche du Qu\u00e9bec-Soci\u00e9t\u00e9 et Culture","doi-asserted-by":"publisher","award":["321850"],"award-info":[{"award-number":["321850"]}],"id":[{"id":"10.13039\/100008240","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008582","name":"McGill University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008582","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["AI &amp; Soc"],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1007\/s00146-023-01673-6","type":"journal-article","created":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T13:03:22Z","timestamp":1682082202000},"page":"2033-2044","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Machine learning in bail decisions and judges\u2019 trustworthiness"],"prefix":"10.1007","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2207-2502","authenticated-orcid":false,"given":"Alexis","family":"Morin-Martel","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,4,21]]},"reference":[{"issue":"2","key":"1673_CR1","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1257\/jep.33.2.31","volume":"33","author":"A Agrawal","year":"2019","unstructured":"Agrawal A, Gans JS, Goldfarb A (2019) Artificial intelligence: the ambiguous labor market impact of automating prediction. J Econ Perspect 33(2):31\u201350. https:\/\/doi.org\/10.1257\/jep.33.2.31","journal-title":"J Econ Perspect"},{"key":"1673_CR2","doi-asserted-by":"crossref","unstructured":"Alfano M, Huijts N (2020) Trust in institutions and governance. In The Routledge handbook of trust and philosophy. Routledge, pp 256\u2013270","DOI":"10.4324\/9781315542294-20"},{"issue":"4","key":"1673_CR3","doi-asserted-by":"publisher","first-page":"1885","DOI":"10.1093\/qje\/qjy012","volume":"133","author":"D Arnold","year":"2018","unstructured":"Arnold D, Dobbie W, Yang CS (2018) Racial bias in bail decisions. Q J Econ 133(4):1885\u20131932. https:\/\/doi.org\/10.1093\/qje\/qjy012","journal-title":"Q J Econ"},{"issue":"2","key":"1673_CR4","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1109\/MTS.2019.2915154","volume":"38","author":"PM Asaro","year":"2019","unstructured":"Asaro PM (2019) AI ethics in predictive policing: from models of threat to an ethics of care. IEEE Technol Soc Mag 38(2):40\u201353. https:\/\/doi.org\/10.1109\/MTS.2019.2915154","journal-title":"IEEE Technol Soc Mag"},{"key":"1673_CR5","doi-asserted-by":"publisher","unstructured":"Ayodele T (2010) Types of machine learning algorithms. In: Zhang Y (eds) New advances in machine learning. InTech, pp 19\u201348. https:\/\/doi.org\/10.5772\/9385","DOI":"10.5772\/9385"},{"key":"1673_CR6","doi-asserted-by":"publisher","unstructured":"Bell A, Solano-Kamaiko I, Nov O, Stoyanovich J (2022) It\u2019s just not that simple: an empirical study of the accuracy-explainability trade-off in machine learning for public policy. 2022 ACM Conference on Fairness, Accountability, and Transparency, pp 248\u2013266. https:\/\/doi.org\/10.1145\/3531146.3533090","DOI":"10.1145\/3531146.3533090"},{"key":"1673_CR7","doi-asserted-by":"crossref","unstructured":"Bottoms A, Tankebe J (2020) Procedural justice, legitimacy, and social contexts. In Procedural justice and relational theory. Routledge, pp 85\u2013110","DOI":"10.4324\/9780429317248-7"},{"issue":"4","key":"1673_CR8","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1017\/glj.2022.32","volume":"23","author":"K Chatziathanasiou","year":"2022","unstructured":"Chatziathanasiou K (2022) Beware the lure of narratives: \u201chungry judges\u201d should not motivate the use of \u201cartificial intelligence\u201d in law. German Law J 23(4):452\u2013464. https:\/\/doi.org\/10.1017\/glj.2022.32","journal-title":"German Law J"},{"issue":"17","key":"1673_CR9","doi-asserted-by":"publisher","first-page":"6889","DOI":"10.1073\/pnas.1018033108","volume":"108","author":"S Danziger","year":"2011","unstructured":"Danziger S, Levav J, Avnaim-Pesso L (2011) Extraneous factors in judicial decisions. Proc Natl Acad Sci 108(17):6889\u20136892. https:\/\/doi.org\/10.1073\/pnas.1018033108","journal-title":"Proc Natl Acad Sci"},{"key":"1673_CR10","first-page":"297","volume":"48","author":"I Demirdag","year":"2020","unstructured":"Demirdag I, Shu S (2020) Insights into the black box: input explainability of algorithmic decisions drives consumer satisfaction in the digital world. NA Adv Consum Res 48:297\u2013298","journal-title":"NA Adv Consum Res"},{"issue":"1","key":"1673_CR11","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1037\/xge0000033","volume":"144","author":"BJ Dietvorst","year":"2015","unstructured":"Dietvorst BJ, Simmons JP, Massey C (2015) Algorithm aversion: People erroneously avoid algorithms after seeing them err. J Exp Psychol Gen 144(1):114\u2013126. https:\/\/doi.org\/10.1037\/xge0000033","journal-title":"J Exp Psychol Gen"},{"key":"1673_CR12","doi-asserted-by":"publisher","unstructured":"Dodge J, Liao QV, Zhang Y, Bellamy RKE, Dugan C (2019) Explaining models: an empirical study of how explanations impact fairness judgment. In: Proceedings of the 24th International Conference on Intelligent User Interfaces, pp 275\u2013285. https:\/\/doi.org\/10.1145\/3301275.3302310","DOI":"10.1145\/3301275.3302310"},{"key":"1673_CR13","unstructured":"Dreyfus HL (1978) What computers can\u2019t do: the limits of artificial intelligence. Harper Collins"},{"key":"1673_CR14","doi-asserted-by":"publisher","unstructured":"Dressel J, Farid H (2018) The accuracy, fairness, and limits of predicting recidivism. Sci Adv 4(1):eaao5580. https:\/\/doi.org\/10.1126\/sciadv.aao5580","DOI":"10.1126\/sciadv.aao5580"},{"key":"1673_CR15","doi-asserted-by":"publisher","DOI":"10.2307\/j.ctvjf9vkt","volume-title":"Justice for hedgehogs","author":"R Dworkin","year":"2011","unstructured":"Dworkin R (2011) Justice for hedgehogs. Belknap Press of Harvard University Press"},{"key":"1673_CR16","doi-asserted-by":"crossref","unstructured":"Goel S, Shroff R, Skeem J, Slobogin C (2021) The accuracy, equity, and jurisprudence of criminal risk assessment. Research handbook on big data law, pp 9\u201328","DOI":"10.4337\/9781788972826.00007"},{"key":"1673_CR17","doi-asserted-by":"publisher","unstructured":"Guttman Z, Hebner Y, Mori K, Balk J (2020) Beyond cash bail: public health, risk assessment, and california senate bill 10. J Sci Pol Govern. https:\/\/doi.org\/10.38126\/JSPG170107","DOI":"10.38126\/JSPG170107"},{"key":"1673_CR18","unstructured":"Heaven WD (2020) Our weird behavior during the pandemic is messing with AI models. MIT Technology Review). https:\/\/Www.Technologyreview.Com\/2020\/05\/11\/1001563\/Covid-Pandemic-Broken-Ai-Machine-Learning-Amazon-Retail-Fraud-Humans-in-the-Loop\/. Accessed 15 June, 2020"},{"key":"1673_CR19","doi-asserted-by":"publisher","first-page":"106635","DOI":"10.1016\/j.chb.2020.106635","volume":"116","author":"M H\u00f6ddinghaus","year":"2021","unstructured":"H\u00f6ddinghaus M, Sondern D, Hertel G (2021) The automation of leadership functions: would people trust decision algorithms? Comput Hum Behav 116:106635. https:\/\/doi.org\/10.1016\/j.chb.2020.106635","journal-title":"Comput Hum Behav"},{"issue":"1","key":"1673_CR20","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1086\/667838","volume":"123","author":"K Jones","year":"2012","unstructured":"Jones K (2012) Trustworthiness. Ethics 123(1):61\u201385. https:\/\/doi.org\/10.1086\/667838","journal-title":"Ethics"},{"key":"1673_CR21","doi-asserted-by":"publisher","DOI":"10.1093\/qje\/qjx032","author":"J Kleinberg","year":"2017","unstructured":"Kleinberg J, Lakkaraju H, Leskovec J, Ludwig J, Mullainathan S (2017a) Human decisions and machine predictions. Q J Econ. https:\/\/doi.org\/10.1093\/qje\/qjx032","journal-title":"Q J Econ"},{"key":"1673_CR22","doi-asserted-by":"crossref","unstructured":"Kleinberg J, Lakkaraju H, Leskovec J, Ludwig J, Mullainathan S (2017b). Human decisions and machine predictions. Unpublished manuscript, Working Paper 23180","DOI":"10.3386\/w23180"},{"key":"1673_CR23","doi-asserted-by":"publisher","unstructured":"Lin Z, Jung J, Goel S, Skeem J (2020) The limits of human predictions of recidivism. Sci Adv 6(7):eaaz0652. https:\/\/doi.org\/10.1126\/sciadv.aaz0652","DOI":"10.1126\/sciadv.aaz0652"},{"key":"1673_CR24","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.obhdp.2018.12.005","volume":"151","author":"JM Logg","year":"2019","unstructured":"Logg JM, Minson JA, Moore DA (2019) Algorithm appreciation: people prefer algorithmic to human judgment. Organ Behav Hum Decis Process 151:90\u2013103. https:\/\/doi.org\/10.1016\/j.obhdp.2018.12.005","journal-title":"Organ Behav Hum Decis Process"},{"issue":"5","key":"1673_CR25","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1111\/j.1740-9713.2016.00960.x","volume":"13","author":"K Lum","year":"2016","unstructured":"Lum K, Isaac W (2016) To predict and serve? Significance 13(5):14\u201319. https:\/\/doi.org\/10.1111\/j.1740-9713.2016.00960.x","journal-title":"Significance"},{"issue":"3","key":"1673_CR26","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1007\/s11023-021-09570-x","volume":"31","author":"J Maclure","year":"2021","unstructured":"Maclure J (2021) AI, explainability and public reason: the argument from the limitations of the human mind. Mind Mach 31(3):421\u2013438. https:\/\/doi.org\/10.1007\/s11023-021-09570-x","journal-title":"Mind Mach"},{"key":"1673_CR27","doi-asserted-by":"publisher","DOI":"10.4324\/9780429317248","author":"D Meyerson","year":"2020","unstructured":"Meyerson D, Mackenzie C, MacDermott T (2020) Procedural justice in law, psychology, and philosophy. Proc Just Relation Theory. https:\/\/doi.org\/10.4324\/9780429317248","journal-title":"Proc Just Relation Theory"},{"issue":"2","key":"1673_CR28","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1016\/j.cjca.2021.09.004","volume":"38","author":"J Petch","year":"2022","unstructured":"Petch J, Di S, Nelson W (2022) Opening the black box: the promise and limitations of explainable machine learning in cardiology. Can J Cardiol 38(2):204\u2013213. https:\/\/doi.org\/10.1016\/j.cjca.2021.09.004","journal-title":"Can J Cardiol"},{"key":"1673_CR29","unstructured":"R. v. J.M.H., 3 SCR 197 (Canada (Federal \u203a 2011). https:\/\/canlii.ca\/t\/fnbb2"},{"key":"1673_CR30","unstructured":"R. v. Singh Garcha, No. 54 (Saskatchewan \u203a March 9, 2004). https:\/\/canlii.ca\/t\/1gvqp"},{"key":"1673_CR31","doi-asserted-by":"publisher","unstructured":"Ribeiro MT, Singh S, Guestrin C (2016) \u201cWhy Should I Trust You?\u201d: explaining the predictions of any classifier. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp 1135\u20131144. https:\/\/doi.org\/10.1145\/2939672.2939778","DOI":"10.1145\/2939672.2939778"},{"issue":"4","key":"1673_CR32","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1007\/s11023-019-09509-3","volume":"29","author":"S Robbins","year":"2019","unstructured":"Robbins S (2019) A misdirected principle with a catch: explicability for AI. Mind Mach 29(4):495\u2013514. https:\/\/doi.org\/10.1007\/s11023-019-09509-3","journal-title":"Mind Mach"},{"key":"1673_CR33","doi-asserted-by":"publisher","unstructured":"Rudin C (2019) Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nat Mach Intell 1(5):206\u2013215. https:\/\/doi.org\/10.1038\/s42256-019-0048-x","DOI":"10.1038\/s42256-019-0048-x"},{"key":"1673_CR34","doi-asserted-by":"publisher","first-page":"103921","DOI":"10.1016\/j.trc.2022.103921","volume":"145","author":"M Shaygan","year":"2022","unstructured":"Shaygan M, Meese C, Li W, Zhao XG, Nejad M (2022) Traffic prediction using artificial intelligence: review of recent advances and emerging opportunities. Transport Res Part c: Emerg Technol 145:103921. https:\/\/doi.org\/10.1016\/j.trc.2022.103921","journal-title":"Transport Res Part c: Emerg Technol"},{"key":"1673_CR35","doi-asserted-by":"publisher","DOI":"10.4324\/9780429317248-9","author":"S Sorial","year":"2020","unstructured":"Sorial S (2020) Legal legitimacy and the relevance of participatory procedures. Proced Just Relation Theory. https:\/\/doi.org\/10.4324\/9780429317248-9","journal-title":"Proced Just Relation Theory"},{"key":"1673_CR37","unstructured":"Stevenson M, Mayson SG (2017) Bail reform: new directions for pretrial detention and release. In: Academy for justice. A Report on Scholarship and Criminal Justice Reform"},{"key":"1673_CR36","doi-asserted-by":"publisher","DOI":"10.4324\/9780429317248-15","author":"N Stoljar","year":"2020","unstructured":"Stoljar N (2020) Racial profiling as pejorative discrimination. Proced Just Relation Theory. https:\/\/doi.org\/10.4324\/9780429317248-15","journal-title":"Proced Just Relation Theory"},{"key":"1673_CR38","doi-asserted-by":"crossref","unstructured":"Tversky A, Kahneman D (1978) Judgment under uncertainty: heuristics and biases: biases in judgments reveal some heuristics of thinking under uncertainty. Uncert Econ 17\u201334","DOI":"10.1016\/B978-0-12-214850-7.50008-5"},{"issue":"1","key":"1673_CR39","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1146\/annurev.psych.57.102904.190038","volume":"57","author":"TR Tyler","year":"2006","unstructured":"Tyler TR (2006) Psychological perspectives on legitimacy and legitimation. Annu Rev Psychol 57(1):375\u2013400. https:\/\/doi.org\/10.1146\/annurev.psych.57.102904.190038","journal-title":"Annu Rev Psychol"},{"key":"1673_CR40","first-page":"841","volume":"31","author":"S Wachter","year":"2017","unstructured":"Wachter S, Mittelstadt B, Russell C (2017) Counterfactual explanations without opening the black box: automated decisions and the GDPR. Harv JL & Tech 31:841","journal-title":"Harv JL & Tech"},{"key":"1673_CR41","doi-asserted-by":"crossref","unstructured":"Waldron J (2011) The rule of law and the importance of procedure. NOMOS: Am Soc Pol Legal Phil 50:3.","DOI":"10.2139\/ssrn.1688491"},{"key":"1673_CR42","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.3170136","author":"AJ Wang","year":"2018","unstructured":"Wang AJ (2018) procedural justice and risk-assessment algorithms. SSRN Electron J. https:\/\/doi.org\/10.2139\/ssrn.3170136","journal-title":"SSRN Electron J"},{"key":"1673_CR43","doi-asserted-by":"publisher","unstructured":"Yin M, Wortman Vaughan J, Wallach H (2019) Understanding the effect of accuracy on trust in machine learning models. In: Proceedings of the 2019 CHI conference on human factors in computing systems, pp 1\u201312. https:\/\/doi.org\/10.1145\/3290605.3300509","DOI":"10.1145\/3290605.3300509"},{"issue":"2","key":"1673_CR44","doi-asserted-by":"publisher","first-page":"022022","DOI":"10.1088\/1742-6596\/1168\/2\/022022","volume":"1168","author":"X Ying","year":"2019","unstructured":"Ying X (2019) An overview of overfitting and its solutions. J Phys Confer Ser 1168(2):022022. https:\/\/doi.org\/10.1088\/1742-6596\/1168\/2\/022022","journal-title":"J Phys Confer Ser"},{"issue":"3","key":"1673_CR45","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1111\/rssa.12227","volume":"180","author":"J Zeng","year":"2017","unstructured":"Zeng J, Ustun B, Rudin C (2017) Interpretable classification models for recidivism prediction. J R Stat Soc A Stat Soc 180(3):689\u2013722. https:\/\/doi.org\/10.1111\/rssa.12227","journal-title":"J R Stat Soc A Stat Soc"},{"issue":"4","key":"1673_CR46","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1007\/s13347-018-0330-6","volume":"32","author":"J Zerilli","year":"2019","unstructured":"Zerilli J, Knott A, Maclaurin J, Gavaghan C (2019) Transparency in algorithmic and human decision-making: is there a double standard? Philos Technol 32(4):661\u2013683. https:\/\/doi.org\/10.1007\/s13347-018-0330-6","journal-title":"Philos Technol"}],"container-title":["AI &amp; SOCIETY"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00146-023-01673-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00146-023-01673-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00146-023-01673-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,8]],"date-time":"2025-04-08T20:47:48Z","timestamp":1744145268000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00146-023-01673-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,21]]},"references-count":46,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["1673"],"URL":"https:\/\/doi.org\/10.1007\/s00146-023-01673-6","relation":{},"ISSN":["0951-5666","1435-5655"],"issn-type":[{"value":"0951-5666","type":"print"},{"value":"1435-5655","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,21]]},"assertion":[{"value":"16 November 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 April 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 April 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The author certify that he has no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}