{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T18:14:29Z","timestamp":1777572869003,"version":"3.51.4"},"reference-count":95,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,6,28]],"date-time":"2024-06-28T00:00:00Z","timestamp":1719532800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,6,28]],"date-time":"2024-06-28T00:00:00Z","timestamp":1719532800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Discov Artif Intell"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Artificial intelligence (AI) is rapidly expanding in myriad industries and systems. This study sought to investigate public trust in using AI in the criminal court process. While previous research has identified factors that influence trust in AI, such as perceived accuracy and transparency of algorithms, less is known about the role of influential leaders\u2014such as judges\u2014in shaping public trust in new technology. This study examined the relationship between locus of control, anthropomorphism, cultural values, and perceived trust in AI. Participants completed a survey assessing their perceptions of trust in AI in determining bail eligibility, bail fines and fees, sentencing length, sentencing fines and fees, and writing legal documents (e.g., findings and disposition). Participants were more likely to trust AI performing financial calculations rather than determining bail eligibility, sentence length, or drafting legal documents. Participants\u2019 comfort with AI in decision-making also depended on their perceptions of judges\u2019 trust in AI, and they expressed concerns about AI perpetuating bias and the need for extensive testing to ensure accuracy. Interestingly, no significant association was found with other participant characteristics (e.g., locus of control, anthropomorphism, or cultural values). This study contributes to the literature by highlighting the role of judges as influential leaders in shaping public trust in AI and examining the influence of individual differences on trust in AI. The findings also help inform the development of recommended practices and ethical guidelines for the responsible use of AI in the courts.<\/jats:p>","DOI":"10.1007\/s44163-024-00142-3","type":"journal-article","created":{"date-parts":[[2024,6,28]],"date-time":"2024-06-28T08:21:37Z","timestamp":1719562897000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Judicial leadership matters (yet again): the association between judge and public trust for artificial intelligence in courts"],"prefix":"10.1007","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7277-7324","authenticated-orcid":false,"given":"Anna","family":"Fine","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7517-1221","authenticated-orcid":false,"given":"Shawn","family":"Marsh","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,6,28]]},"reference":[{"issue":"3","key":"142_CR1","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1002\/rhc3.12219","volume":"12","author":"SC Ahluwalia","year":"2021","unstructured":"Ahluwalia SC, Edelen MO, Qureshi N, Etchegaray JM. Trust in experts, not trust in national leadership, leads to greater uptake of recommended actions during the COVID-19 pandemic. Risk Hazards Crisis Public Policy. 2021;12(3):283\u2013302. https:\/\/doi.org\/10.1002\/rhc3.12219.","journal-title":"Risk Hazards Crisis Public Policy"},{"key":"142_CR2","first-page":"254","volume-title":"Ethics of data and analytics","author":"J Angwin","year":"2016","unstructured":"Angwin J, Larson J, Mattu S, Kirchner L. Machine bias. In: Ethics of data and analytics. Boca Raton: Auerbach Publications; 2016. p. 254\u201364."},{"key":"142_CR3","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/j.chb.2018.03.051","volume":"85","author":"T Araujo","year":"2018","unstructured":"Araujo T. Living up to the chatbot hype: the influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions. Comput Hum Behav. 2018;85:183\u20139. https:\/\/doi.org\/10.1016\/j.chb.2018.03.051.","journal-title":"Comput Hum Behav"},{"key":"142_CR4","doi-asserted-by":"publisher","unstructured":"Antinucci M. EU Ethical Charter on the use of artificial intelligence in judicial systems with a part of the law being established on blockchain as a Trojan horse anti-counterfeiting in a global perspective. In: Courier of Kutafin Moscow State Law University (MSAL). 2020; 2: 36\u201342. https:\/\/doi.org\/10.17803\/2311-5998.2020.66.2.036-042.","DOI":"10.17803\/2311-5998.2020.66.2.036-042"},{"key":"142_CR5","unstructured":"Barabas, Dinakar K, Ito J, Virza M, Zittrain J. Interventions over predictions: reframing the ethical debate for actuarial risk assessment. arXiv.org. 2018."},{"key":"142_CR6","doi-asserted-by":"crossref","unstructured":"Bauguess SW. The role of big data, machine learning, and AI in assessing risks: a regulatory perspective. U.S. Securities and Exchange Commission. 2017. https:\/\/www.sec.gov\/news\/speech\/bauguess-bigdata-ai.","DOI":"10.2139\/ssrn.3226514"},{"key":"142_CR7","doi-asserted-by":"publisher","unstructured":"Bauman MJ, Boxer KS, Lin TY, Salomon E, Naveed H, Haynes L, Walsh J, Helsby J, Yoder S, Sullivan R, Schneweis C. Reducing incarceration through prioritized interventions. In: Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies. pp. 1\u20138. 2018. https:\/\/doi.org\/10.1145\/3209811.3209869.","DOI":"10.1145\/3209811.3209869"},{"key":"142_CR8","unstructured":"Brown S. Machine learning, explained. MIT Management Sloan School. 2021; https:\/\/mitsloan.mit.edu\/ideas-made-to-matter\/machine-learning-explained."},{"issue":"1","key":"142_CR9","doi-asserted-by":"publisher","first-page":"29","DOI":"10.2307\/3219881","volume":"56","author":"P Burstein","year":"2003","unstructured":"Burstein P. The impact of public opinion on public policy: a review and an agenda. Polit Res Q. 2003;56(1):29\u201340. https:\/\/doi.org\/10.2307\/3219881.","journal-title":"Polit Res Q"},{"key":"142_CR10","unstructured":"Buskey B, Woods A. Making sense of pretrial risk assessments. National Association of Defense Lawyers. 2018. https:\/\/www.nacdl.org\/Article\/June2018-MakingSenseofPretrialRiskAsses."},{"key":"142_CR11","unstructured":"Canhoto A. Quality and ethical concerns over the use of ChatGPT to analyse interview data in research. Ana Conhoto. 2023. https:\/\/anacanhoto.com\/2023\/04\/10\/quality-and-ethical-concerns-over-the-use-of-chatgpt-to-analyse-interview-data-in-research\/."},{"issue":"2","key":"142_CR12","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1016\/j.jcps.2009.12.008","volume":"20","author":"J Chandler","year":"2010","unstructured":"Chandler J, Schwarz N. Use does not wear ragged the fabric of friendship: thinking of objects as alive makes people less willing to replace them. J Consum Psychol. 2010;20(2):138\u201345. https:\/\/doi.org\/10.1016\/j.jcps.2009.12.008.","journal-title":"J Consum Psychol"},{"issue":"1","key":"142_CR13","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1080\/10510974.2020.1807380","volume":"72","author":"YNK Chen","year":"2021","unstructured":"Chen YNK, Wen CHR. Impacts of attitudes toward government and corporations on public trust in artificial intelligence. Commun Stud. 2021;72(1):115\u201331. https:\/\/doi.org\/10.1080\/10510974.2020.1807380.","journal-title":"Commun Stud"},{"issue":"1","key":"142_CR14","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1037\/a0028596","volume":"139","author":"C Cheng","year":"2013","unstructured":"Cheng C, Cheung SF, Chio JHM, Chan MPS. Cultural meaning of perceived control: a meta-analysis of locus of control and psychological symptoms across 18 cultural regions. Psychol Bull. 2013;139(1):152. https:\/\/doi.org\/10.1037\/a0028596.","journal-title":"Psychol Bull"},{"key":"142_CR15","unstructured":"Cherson J. Policy position brief: On pretrial algorithms (risk assessments). The Bail Project. 2022. https:\/\/bailproject.org\/policy\/pretrial-algorithms\/."},{"key":"142_CR16","unstructured":"Chesterman P. Leveraging ChatGPT for qualitative analysis: Exploring the power of generative AI. Ethos. 2023. https:\/\/ethosapp.com\/blog\/leveraging-chatgpt-for-qualitative-analysis-exploring-the-power-of-generative-ai\/."},{"key":"142_CR17","unstructured":"Chohlas-Wood A. Understanding risk assessment instruments in criminal justice. Brookings. 2020. https:\/\/www.brookings.edu\/articles\/understanding-risk-assessment-instruments-in-criminal-justice\/#:~:text=Second%2C%20any%20algorithm%20used%20in,over%20human%20decision%2Dmaking%20processes."},{"key":"142_CR18","unstructured":"Code for America. Los Angeles County DA & Code for America Announce Dismissals of 66,000 Marijuana Convictions, Marking Completion of Five-County Clear My Record Pilot. Code for America. 2020. https:\/\/codeforamerica.org\/news\/los-angeles-county-da-code-for-america-announce-dismissals-of-66-000-marijuana-convictions-marking-completion-of-five-county-clear-my-record-pilot\/."},{"issue":"5\u20136","key":"142_CR19","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1016\/j.ijlp.2012.09.016","volume":"35","author":"ML Commons","year":"2012","unstructured":"Commons ML, Miller PM, Li EY, Gutheil TG. Forensic experts\u2019 perceptions of expert bias. Int J Law Psychiatry. 2012;35(5\u20136):362\u201371. https:\/\/doi.org\/10.1016\/j.ijlp.2012.09.016.","journal-title":"Int J Law Psychiatry"},{"key":"142_CR20","unstructured":"Copeland B. Artificial intelligence. Encyclopedia Britannica. 2022. https:\/\/www.britannica.com\/technology\/artificial-intelligence."},{"issue":"3","key":"142_CR21","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/0010-0277(89)90023-1","volume":"31","author":"L Cosmides","year":"1989","unstructured":"Cosmides L. The logic of social exchange: has natural selection shaped how humans reason? Studies with the Wason selection task. Cognition. 1989;31(3):187\u2013276. https:\/\/doi.org\/10.1016\/0010-0277(89)90023-1.","journal-title":"Cognition"},{"issue":"4409","key":"142_CR22","doi-asserted-by":"publisher","first-page":"997","DOI":"10.1126\/science.2648573","volume":"205","author":"RM Dawes","year":"1979","unstructured":"Dawes RM, Faust D, Meehl PE. Clinical versus actuarial judgment. Science. 1979;205(4409):997\u20131003. https:\/\/doi.org\/10.1126\/science.2648573.","journal-title":"Science"},{"issue":"3","key":"142_CR23","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1037\/xap0000092","volume":"22","author":"EJ de Visser","year":"2016","unstructured":"de Visser EJ, Monfort SS, McKendrick R, Smith MA, McKnight PE, Krueger F, Parasuraman R. Almost human: anthropomorphism increases trust resilience in cognitive agents. J Exp Psychol Appl. 2016;22(3):331. https:\/\/doi.org\/10.1037\/xap0000092.","journal-title":"J Exp Psychol Appl"},{"issue":"4","key":"142_CR24","doi-asserted-by":"publisher","first-page":"994","DOI":"10.1111\/j.0038-4941.2004.00255.x","volume":"85","author":"S Demuth","year":"2004","unstructured":"Demuth S, Steffensmeier D. Ethnicity effects on sentence outcomes in large urban courts: comparisons among White, Black, and Hispanic defendants. Soc Sci Q. 2004;85(4):994\u20131011. https:\/\/doi.org\/10.1111\/j.0038-4941.2004.00255.x.","journal-title":"Soc Sci Q"},{"issue":"2","key":"142_CR25","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1525\/sp.2004.51.2.222","volume":"51","author":"S Demuth","year":"2004","unstructured":"Demuth S, Steffensmeier D. The impact of gender and race-ethnicity in the pretrial release process. Soc Probl. 2004;51(2):222\u201342. https:\/\/doi.org\/10.1525\/sp.2004.51.2.222.","journal-title":"Soc Probl"},{"key":"142_CR26","first-page":"1","volume":"31","author":"DR Desai","year":"2017","unstructured":"Desai DR, Kroll JA. Trust but verify: a guide to algorithms and the law. Harvard J Law Technol. 2017;31:1\u201364.","journal-title":"Harvard J Law Technol"},{"key":"142_CR27","doi-asserted-by":"publisher","unstructured":"Dietvorst BJ, Simmons J, Massey C. Understanding algorithm aversion: forecasters erroneously avoid algorithms after seeing them err. In: Academy of Management Proceedings. Briarcliff Manor, Ny 10510: Academy of Management. 2015; 2014(1): 12227. https:\/\/doi.org\/10.5465\/ambpp.2014.12227abstract.","DOI":"10.5465\/ambpp.2014.12227abstract"},{"issue":"5","key":"142_CR28","doi-asserted-by":"publisher","first-page":"680","DOI":"10.1177\/0146167204271570","volume":"31","author":"J Ehrlinger","year":"2005","unstructured":"Ehrlinger J, Gilovich T, Ross L. Peering into the bias blind spot: People\u2019s assessments of bias in themselves and others. Pers Soc Psychol Bull. 2005;31(5):680\u201392. https:\/\/doi.org\/10.1177\/0146167204271570.","journal-title":"Pers Soc Psychol Bull"},{"issue":"2","key":"142_CR29","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1007\/s10111-018-0512-0","volume":"21","author":"S Erebak","year":"2019","unstructured":"Erebak S, Turgut T. Caregivers\u2019 attitudes toward potential robot coworkers in elder care. Cogn Technol Work. 2019;21(2):327\u201336. https:\/\/doi.org\/10.1007\/s10111-018-0512-0.","journal-title":"Cogn Technol Work"},{"key":"142_CR30","doi-asserted-by":"publisher","unstructured":"Faul F, Erdfelder E, Lang AG,  Buchner A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 2007;39(2):175\u2013191. https:\/\/doi.org\/10.3758\/BF03193146.","DOI":"10.3758\/BF03193146"},{"issue":"1","key":"142_CR31","first-page":"135","volume":"28","author":"A Fiechuk","year":"2019","unstructured":"Fiechuk A. The use of AI assistants in the courtroom and overcoming privacy concerns. Widener Commonwealth Law Rev. 2019;28(1):135\u201368.","journal-title":"Widener Commonwealth Law Rev"},{"key":"142_CR32","first-page":"915","volume-title":"The handbook of social psychology","author":"AP Fiske","year":"1998","unstructured":"Fiske AP, Kitayama S, Markus HR, Nisbett RE. The cultural matrix of social psychology. In: Gilbert DT, Fiske ST, Lindzey G, editors. The handbook of social psychology. McGraw-Hill; 1998. p. 915\u201381."},{"key":"142_CR33","doi-asserted-by":"publisher","unstructured":"Fjeld J, Achten N, Hilligoss H, Nagy A, Srikumar M. Principled artificial intelligence: mapping consensus in ethical and rights-based approaches to principles for AI. Berkman Klein Center Research Publication, (2020-1). 2020. https:\/\/doi.org\/10.2139\/ssrn.3518482.","DOI":"10.2139\/ssrn.3518482"},{"key":"142_CR34","unstructured":"Gecker J. San Francisco prosecutors turn to AI to reduce racial bias. The Washington Post. 2019. https:\/\/www.washingtonpost.com\/business\/economy\/san-francisco-prosecutors-to-use-artificial-intelligence-to-reduce-racial-bias-in-courts\/2019\/06\/12\/b37d9a04-8d58-11e9-b08e-cfd89bd36d4e_story.html."},{"key":"142_CR35","unstructured":"Geisen E. Improve data quality by using a commitment request instead of attention checks. Qualtrics. 2022. https:\/\/www.qualtrics.com\/blog\/attention-checks-and-data-quality\/."},{"key":"142_CR36","volume-title":"How we know what isn\u2019t so: the fallibility of human reason in everyday life","author":"T Gilovich","year":"1991","unstructured":"Gilovich T. How we know what isn\u2019t so: the fallibility of human reason in everyday life. India: Free Press; 1991."},{"key":"142_CR37","doi-asserted-by":"publisher","unstructured":"Glaze K, Ho DE, Tsang C. Artificial intelligence for adjudication: the social security administration and AI governance. In: The Oxford Handbook of AI Governance. 2021; Oxford: Oxford University Press. https:\/\/doi.org\/10.1093\/oxfordhb\/9780197579329.013.46.","DOI":"10.1093\/oxfordhb\/9780197579329.013.46"},{"issue":"2","key":"142_CR38","doi-asserted-by":"publisher","first-page":"627","DOI":"10.5465\/annals.2018.0057","volume":"14","author":"E Glikson","year":"2020","unstructured":"Glikson E, Woolley AW. Human trust in artificial intelligence: review of empirical research. Acad Manage Ann. 2020;14(2):627\u201360. https:\/\/doi.org\/10.5465\/annals.2018.0057.","journal-title":"Acad Manage Ann"},{"issue":"2","key":"142_CR39","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1037\/1076-8971.2.2.293","volume":"2","author":"WM Grove","year":"1996","unstructured":"Grove WM, Meehl RE. Comparative efficiency of informal (subjective, impressionistic) and formal (mechanical, algorithmic) prediction procedures: the clinical-statistical controversy. Psychol Public Policy Law. 1996;2(2):293\u2013323. https:\/\/doi.org\/10.1037\/1076-8971.2.2.293.","journal-title":"Psychol Public Policy Law"},{"issue":"1","key":"142_CR40","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1037\/1040-3590.12.1.19","volume":"12","author":"WM Grove","year":"2000","unstructured":"Grove WM, Zald DH, Lebow BS, Snitz BE, Nelson C. Clinical versus mechanical prediction: a meta-analysis. Psychol Assess. 2000;12(1):19\u201330. https:\/\/doi.org\/10.1037\/1040-3590.12.1.19.","journal-title":"Psychol Assess"},{"issue":"5","key":"142_CR41","doi-asserted-by":"publisher","first-page":"517","DOI":"10.1177\/0018720811417254","volume":"53","author":"PA Hancock","year":"2011","unstructured":"Hancock PA, Billings DR, Schaefer KE, Chen JY, De Visser EJ, Parasuraman R. A meta-analysis of factors affecting trust in human\u2013robot interaction. Hum Factors. 2011;53(5):517\u201327. https:\/\/doi.org\/10.1177\/0018720811417254.","journal-title":"Hum Factors"},{"key":"142_CR42","doi-asserted-by":"crossref","unstructured":"Harris J. Effective strategies for changing public opinion: a literature review. Sentience Institute. 2021; https:\/\/www.sentienceinstitute.org\/public-opinion.","DOI":"10.31235\/osf.io\/pg8sk"},{"issue":"2","key":"142_CR43","first-page":"8","volume":"70","author":"P Harris","year":"2006","unstructured":"Harris P. What community supervision officers need to know about actuarial risk assessment and clinical judgment. Federal Prob. 2006;70(2):8\u201314.","journal-title":"Federal Prob"},{"issue":"2\u20133","key":"142_CR44","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1017\/S0140525X0999152X","volume":"33","author":"J Henrich","year":"2010","unstructured":"Henrich J, Heine SJ, Norenzayan A. The weirdest people in the world? Behav Brain Sci. 2010;33(2\u20133):61\u201383. https:\/\/doi.org\/10.1017\/S0140525X0999152X.","journal-title":"Behav Brain Sci"},{"key":"142_CR45","volume-title":"Culture's consequences: comparing values, behaviors, institutions and organizations across nations","author":"G Hofstede","year":"2001","unstructured":"Hofstede G. Culture\u2019s consequences: comparing values, behaviors, institutions and organizations across nations. USA: Sage Publications; 2001."},{"issue":"1","key":"142_CR46","doi-asserted-by":"publisher","first-page":"2307","DOI":"10.9707\/2307-0919.1014","volume":"2","author":"G Hofstede","year":"2011","unstructured":"Hofstede G. Dimensionalizing cultures: the Hofstede model in context. Online Readings Psychol Cult. 2011;2(1):2307\u2013919. https:\/\/doi.org\/10.9707\/2307-0919.1014.","journal-title":"Online Readings Psychol Cult"},{"key":"142_CR47","unstructured":"Iguazio. What is model accuracy in machine learning? Iguazio. 2023. https:\/\/www.iguazio.com\/glossary\/model-accuracy-in-ml\/#:~:text=AI%20accuracy%20is%20the%20percentage,is%20often%20abbreviated%20as%20ACC."},{"issue":"1","key":"142_CR48","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1093\/qje\/qjx032","volume":"133","author":"J Kleinberg","year":"2018","unstructured":"Kleinberg J, Lakkaraju H, Leskovec J, Ludwig J, Mullainathan S. Human decisions and machine predictions. Q J Econ. 2018;133(1):237\u201393. https:\/\/doi.org\/10.1093\/qje\/qjx032.","journal-title":"Q J Econ"},{"key":"142_CR49","first-page":"537","volume":"91","author":"C Klingele","year":"2015","unstructured":"Klingele C. The promises and perils of evidence-based corrections. Notre Dame L Rev. 2015;91:537.","journal-title":"Notre Dame L Rev"},{"key":"142_CR50","unstructured":"Krogue K. Artificial intelligence is here to stay, but consumer trust is a must for AI in business. Forbes. 2017. https:\/\/www.forbes.com\/sites\/kenkrogue\/2017\/09\/11\/artificial-intelligence-is-here-to-stay-but-consumer-trust-is-a-must-for-ai-in-business\/?sh=6801a857776e."},{"issue":"1","key":"142_CR51","doi-asserted-by":"publisher","first-page":"4569","DOI":"10.1038\/s41598-023-31341-0","volume":"13","author":"S Kr\u00fcgel","year":"2023","unstructured":"Kr\u00fcgel S, Ostermaier A, Uhl M. ChatGPT\u2019s inconsistent moral advice influences users\u2019 judgment. Sci Rep. 2023;13(1):4569. https:\/\/doi.org\/10.1038\/s41598-023-31341-0.","journal-title":"Sci Rep"},{"key":"142_CR52","doi-asserted-by":"publisher","first-page":"480","DOI":"10.1037\/0033-2909.108.3.480","volume":"108","author":"Z Kunda","year":"1990","unstructured":"Kunda Z. The case for motivated reasoning. Psychol Bull. 1990;108:480\u201398. https:\/\/doi.org\/10.1037\/0033-2909.108.3.480.","journal-title":"Psychol Bull"},{"key":"142_CR53","unstructured":"Lee NT, Lai S. The U.S. can improve its AI governance strategy by addressing online biases. Brookings. 2022. https:\/\/www.brookings.edu\/blog\/techtank\/2022\/05\/17\/the-u-s-can-improve-its-ai-governance-strategy-by-addressing-online-biases\/."},{"key":"142_CR54","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. Algorithm appreciation: people prefer algorithmic to human judgment. Organ Behav Hum Decis Process. 2019;151:90\u2013103. https:\/\/doi.org\/10.1016\/j.obhdp.2018.12.005.","journal-title":"Organ Behav Hum Decis Process"},{"issue":"1","key":"142_CR55","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1007\/s43681-022-00137-9","volume":"2","author":"MdA Malek","year":"2022","unstructured":"Malek MdA. Criminal courts\u2019 artificial intelligence: the way it reinforces bias and discrimination. AI and Ethics. 2022;2(1):233\u201345. https:\/\/doi.org\/10.1007\/s43681-022-00137-9.","journal-title":"AI and Ethics"},{"issue":"2","key":"142_CR56","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1037\/0033-295X.98.2.224","volume":"98","author":"HR Markus","year":"1991","unstructured":"Markus HR, Kitayama S. Culture and the self: implications for cognition, emotion, and motivation. Psychol Rev. 1991;98(2):224. https:\/\/doi.org\/10.1037\/0033-295X.98.2.224.","journal-title":"Psychol Rev"},{"key":"142_CR57","first-page":"490","volume":"127","author":"SG Mayson","year":"2017","unstructured":"Mayson SG. Dangerous defendants. Yale Law J. 2017;127:490.","journal-title":"Yale Law J"},{"key":"142_CR58","doi-asserted-by":"publisher","first-page":"705809","DOI":"10.3389\/fsoc.2021.705809","volume":"6","author":"M Misamer","year":"2021","unstructured":"Misamer M, Signerski-Krieger J, Bartels C, Belz M. Internal locus of control and sense of coherence decrease during the COVID-19 pandemic: a survey of students and professionals in social work. Front Sociol. 2021;6:705809\u2013705809. https:\/\/doi.org\/10.3389\/fsoc.2021.705809.","journal-title":"Front Sociol"},{"key":"142_CR59","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1146\/annurev-clinpsy-021815-092945","volume":"12","author":"J Monahan","year":"2016","unstructured":"Monahan J, Skeem JL. Risk assessment in criminal sentencing. Annu Rev Clin Psychol. 2016;12:489\u2013513. https:\/\/doi.org\/10.1146\/annurev-clinpsy-021815-092945.","journal-title":"Annu Rev Clin Psychol"},{"key":"142_CR60","doi-asserted-by":"publisher","DOI":"10.1093\/oso\/9780195138825.001.0001","volume-title":"Rethinking risk assessment","author":"J Monahan","year":"2001","unstructured":"Monahan J, Steadman HJ, Silver E, Appelbaum PS, Clark Robbins P, Mulvey EP, Roth LH, Grisso T, Banks S. Rethinking risk assessment. Oxford University Press; 2001."},{"key":"142_CR61","first-page":"45","volume":"111","author":"AD Morantz","year":"2008","unstructured":"Morantz AD. Mining mining data: bringing empirical analysis to bear on the regulation of safety and health in us mining. West Virgina Law Rev. 2008;111:45.","journal-title":"West Virgina Law Rev"},{"issue":"4","key":"142_CR62","doi-asserted-by":"publisher","first-page":"783","DOI":"10.1037\/0022-006X.62.4.783","volume":"62","author":"D Mossman","year":"1994","unstructured":"Mossman D. Assessing predictions of violence: being accurate about accuracy. J Consult Clin Psychol. 1994;62(4):783. https:\/\/doi.org\/10.1037\/0022-006X.62.4.783.","journal-title":"J Consult Clin Psychol"},{"issue":"1","key":"142_CR63","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1037\/law0000077","volume":"22","author":"TMS Neal","year":"2016","unstructured":"Neal TMS, Brodsky SL. Forensic psychologists\u2019 perceptions of bias and potential correction strategies in forensic mental health evaluations. Psychol Public Policy Law. 2016;22(1):58\u201376. https:\/\/doi.org\/10.1037\/law0000077.","journal-title":"Psychol Public Policy Law"},{"key":"142_CR64","doi-asserted-by":"publisher","first-page":"663","DOI":"10.1007\/s00146-019-00924-9","volume":"35","author":"H Neri","year":"2020","unstructured":"Neri H, Cozman F. The role of experts in the public perception of risk of artificial intelligence. AI Soc. 2020;35:663\u201373. https:\/\/doi.org\/10.1007\/s00146-019-00924-9.","journal-title":"AI Soc"},{"issue":"1","key":"142_CR65","doi-asserted-by":"publisher","first-page":"23","DOI":"10.2307\/1960777","volume":"81","author":"BI Page","year":"1987","unstructured":"Page BI, Shapiro RY, Dempsey GR. What moves public opinion? Am Polit Sci Rev. 1987;81(1):23\u201343. https:\/\/doi.org\/10.2307\/1960777.","journal-title":"Am Polit Sci Rev"},{"key":"142_CR66","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.jesp.2017.01.006","volume":"70","author":"E Peer","year":"2017","unstructured":"Peer E, Brandimarte L, Samat S, Acquisti A. Beyond the turk: alternative platforms for crowdsourcing behavioral research. J Exp Soc Psychol. 2017;70:153\u201363. https:\/\/doi.org\/10.1016\/j.jesp.2017.01.006.","journal-title":"J Exp Soc Psychol"},{"issue":"3","key":"142_CR67","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1177\/0146167202286008","volume":"28","author":"E Pronin","year":"2002","unstructured":"Pronin E, Lin DY, Ross L. The bias blind spot: Perceptions of bias in self versus others. Pers Soc Psychol Bull. 2002;28(3):369\u201381. https:\/\/doi.org\/10.1177\/0146167202286008.","journal-title":"Pers Soc Psychol Bull"},{"key":"142_CR68","doi-asserted-by":"publisher","DOI":"10.1016\/j.jrt.2020.100005","volume":"4","author":"R Rodrigues","year":"2020","unstructured":"Rodrigues R. Legal and human rights issues of AI: gaps, challenges and vulnerabilities. J Respons Technol. 2020;4: 100005. https:\/\/doi.org\/10.1016\/j.jrt.2020.100005.","journal-title":"J Respons Technol"},{"key":"142_CR69","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1007\/BF01065249","volume":"1","author":"PH Rossi","year":"1985","unstructured":"Rossi PH, Simpson JE, Miller JL. Beyond crime seriousness: fitting the punishment to the crime. J Quant Criminol. 1985;1:59\u201390. https:\/\/doi.org\/10.1007\/BF01065249.","journal-title":"J Quant Criminol"},{"issue":"1","key":"142_CR70","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1037\/h0092976","volume":"80","author":"JB Rotter","year":"1966","unstructured":"Rotter JB. Generalized expectancies for internal versus external control of reinforcement. Psychol Monogr Gen Appl. 1966;80(1):1. https:\/\/doi.org\/10.1037\/h0092976.","journal-title":"Psychol Monogr Gen Appl"},{"key":"142_CR71","volume-title":"Applications of a social learning theory of personality","author":"JB Rotter","year":"1972","unstructured":"Rotter JB, Chance JE, Phares EJ. Applications of a social learning theory of personality. Rinehart and Winston: Holt; 1972."},{"issue":"8","key":"142_CR72","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2020.e04572","volume":"6","author":"NN Sharan","year":"2020","unstructured":"Sharan NN, Romano DM. The effects of personality and locus of control on trust in humans versus artificial intelligence. Heliyon. 2020;6(8): e04572. https:\/\/doi.org\/10.1016\/j.heliyon.2020.e04572.","journal-title":"Heliyon"},{"key":"142_CR73","doi-asserted-by":"publisher","DOI":"10.1109\/TEM.2022.3157976","author":"S Sharma","year":"2022","unstructured":"Sharma S, Islam N, Singh G, Dhir A. Why do retail customers adopt artificial intelligence (AI) based autonomous decision-making systems? IEEE Trans Eng Manage. 2022. https:\/\/doi.org\/10.1109\/TEM.2022.3157976.","journal-title":"IEEE Trans Eng Manage"},{"issue":"1","key":"142_CR74","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1037\/h0034216","volume":"26","author":"SJ Sherman","year":"1973","unstructured":"Sherman SJ. Internal-external control and its relationship to attitude change under different social influence techniques. J Pers Soc Psychol. 1973;26(1):23\u20139. https:\/\/doi.org\/10.1037\/h0034216.","journal-title":"J Pers Soc Psychol"},{"key":"142_CR75","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2019.102061","volume":"52","author":"D Shin","year":"2020","unstructured":"Shin D, Zhong B, Biocca FA. Beyond user experience: what constitutes algorithmic experiences? Int J Inf Manage. 2020;52: 102061. https:\/\/doi.org\/10.1016\/j.ijinfomgt.2019.102061.","journal-title":"Int J Inf Manage"},{"issue":"2","key":"142_CR76","first-page":"47","volume":"31","author":"K Siau","year":"2018","unstructured":"Siau K, Wang W. Building trust in artificial intelligence, machine learning, and robotics. Cutter Bus Technol J. 2018;31(2):47\u201353.","journal-title":"Cutter Bus Technol J"},{"key":"142_CR77","first-page":"1067","volume":"52","author":"R Simmons","year":"2018","unstructured":"Simmons R. Big data, machine judges, and the legitimacy of the criminal justice system. UC Davis L Rev. 2018;52:1067.","journal-title":"UC Davis L Rev"},{"key":"142_CR78","doi-asserted-by":"crossref","unstructured":"Smith V. Maryland, 442 U.S. 735 (1979).","DOI":"10.1128\/jb.137.2.735-739.1979"},{"issue":"1","key":"142_CR79","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1111\/j.1745-9125.2000.tb00891.x","volume":"38","author":"C Spohn","year":"2000","unstructured":"Spohn C, Holleran D. The imprisonment penalty paid by young, unemployed black and Hispanic male offenders. Criminology. 2000;38(1):281\u2013306. https:\/\/doi.org\/10.1111\/j.1745-9125.2000.tb00891.x.","journal-title":"Criminology"},{"key":"142_CR80","first-page":"803","volume":"66","author":"SB Starr","year":"2014","unstructured":"Starr SB. Evidence-based sentencing and the scientific rationalization of discrimination. Stanford Law Rev. 2014;66:803.","journal-title":"Stanford Law Rev"},{"key":"142_CR81","doi-asserted-by":"publisher","unstructured":"Teo T, Milutinovi\u0107 V, Zhou M,  Bankovi\u0107 D. Technology Acceptance Model Instrument. PsycTESTS. 2017. https:\/\/doi.org\/10.1037\/t64926-000.","DOI":"10.1037\/t64926-000"},{"issue":"1","key":"142_CR82","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1080\/08874417.2003.11647554","volume":"44","author":"JB Thatcher","year":"2003","unstructured":"Thatcher JB, Stepina LP, Srite M, Liu Y. Culture, overload and personal innovativeness with information technology: extending the nomological net. J Comput Inf Syst. 2003;44(1):74\u201381. https:\/\/doi.org\/10.1080\/08874417.2003.11647554.","journal-title":"J Comput Inf Syst"},{"key":"142_CR83","unstructured":"The US Department of the Treasury. Federal agency data mining report. The US Department of the Treasury. 2009. https:\/\/www.treasury.gov\/privacy\/annual-reports\/Documents\/FY2008\/DataMiningReport.pdf."},{"issue":"1","key":"142_CR84","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1007\/BF02885880","volume":"30","author":"KB Turner","year":"2005","unstructured":"Turner KB, Johnson JB. A comparison of bail amounts for Hispanics, Whites, and African Americans: a single county analysis. Am J Crim Justice. 2005;30(1):35\u201353. https:\/\/doi.org\/10.1007\/BF02885880.","journal-title":"Am J Crim Justice"},{"issue":"3","key":"142_CR85","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1207\/s15327957pspr0803_5","volume":"8","author":"JM Twenge","year":"2004","unstructured":"Twenge JM, Zhang L, Im C. It\u2019s beyond my control: a cross-temporal meta-analysis of increasing externality in locus of control, 1960\u20132002. Personal Soc Psychol Rev. 2004;8(3):308\u201319. https:\/\/doi.org\/10.1207\/s15327957pspr0803_5.","journal-title":"Personal Soc Psychol Rev"},{"key":"142_CR86","unstructured":"US General Accounting Office. Data mining: Federal efforts cover a wide range of uses. Report to the Ranking Minority Member, Subcommittee on Financial Management, the Budget, and International Security. 2004. https:\/\/www.gao.gov\/assets\/gao-04-548.pdf."},{"issue":"4","key":"142_CR87","doi-asserted-by":"publisher","first-page":"1607","DOI":"10.1007\/s13347-021-00477-0","volume":"34","author":"WJ von Eschenbach","year":"2021","unstructured":"von Eschenbach WJ. Transparency and the black box problem: why we do not trust AI. Philos Technol. 2021;34(4):1607\u201322. https:\/\/doi.org\/10.1007\/s13347-021-00477-0.","journal-title":"Philos Technol"},{"key":"142_CR88","doi-asserted-by":"crossref","unstructured":"Wachter S, Mittelstadt B. A right to reasonable inferences: re-thinking data protection law in the age of big data and AI.\u00a0Columbia Bus Law Rev. 2019; 494. https:\/\/ssrn.com\/abstract=3248829.","DOI":"10.31228\/osf.io\/mu2kf"},{"issue":"3","key":"142_CR89","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1007\/s11023-019-09506-6","volume":"29","author":"D Watson","year":"2019","unstructured":"Watson D. The rhetoric and reality of anthropomorphism in artificial intelligence. Mind Mach. 2019;29(3):417\u201340. https:\/\/doi.org\/10.1007\/s11023-019-09506-6.","journal-title":"Mind Mach"},{"key":"142_CR90","volume-title":"Punishment and inequality in America","author":"B Western","year":"2006","unstructured":"Western B. Punishment and inequality in America. Russell Sage Foundation; 2006."},{"issue":"3","key":"142_CR91","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1177\/1745691610369336","volume":"5","author":"A Waytz","year":"2010","unstructured":"Waytz A, Cacioppo J, Epley N. Who sees human? The stability and importance of individual differences in anthropomorphism. Perspect Psychol Sci. 2010;5(3):219\u201332. https:\/\/doi.org\/10.1177\/1745691610369336.","journal-title":"Perspect Psychol Sci"},{"key":"142_CR92","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.jesp.2014.01.005","volume":"52","author":"A Waytz","year":"2014","unstructured":"Waytz A, Heafner J, Epley N. The mind in the machine: anthropomorphism increases trust in an autonomous vehicle. J Exp Soc Psychol. 2014;52:113\u20137. https:\/\/doi.org\/10.1016\/j.jesp.2014.01.005.","journal-title":"J Exp Soc Psychol"},{"key":"142_CR93","unstructured":"Wihbey J. The Supreme Court, public opinion and decision-making: Research roundup. The Journalist\u2019s Resource. 2013. https:\/\/journalistsresource.org\/politics-and-government\/research-roundup-supreme-court-public-opinion\/#:~:text=."},{"issue":"3\u20134","key":"142_CR94","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1080\/08961530.2011.578059","volume":"23","author":"B Yoo","year":"2011","unstructured":"Yoo B, Donthu N, Lenartowicz T. Measuring Hofstede\u2019s five dimensions of cultural values at the individual level: development and validation of CVSCALE. J Int Consum Market. 2011;23(3\u20134):193\u2013210. https:\/\/doi.org\/10.1080\/08961530.2011.578059.","journal-title":"J Int Consum Market"},{"key":"142_CR95","doi-asserted-by":"publisher","unstructured":"Zhang B, Dafoe A. Artificial Intelligence: American Attitudes and Trends. Center for the Governance of AI Future of Humanity Institute University of Oxford. 2019. https:\/\/doi.org\/10.2139\/ssrn.3312874.","DOI":"10.2139\/ssrn.3312874"}],"container-title":["Discover Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44163-024-00142-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44163-024-00142-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44163-024-00142-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,28]],"date-time":"2024-06-28T08:35:38Z","timestamp":1719563738000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44163-024-00142-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,28]]},"references-count":95,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["142"],"URL":"https:\/\/doi.org\/10.1007\/s44163-024-00142-3","relation":{},"ISSN":["2731-0809"],"issn-type":[{"value":"2731-0809","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,6,28]]},"assertion":[{"value":"21 February 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 June 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 June 2024","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 authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"44"}}