Skip to main content

Advertisement

Log in

Artificial Intelligence, Algorithms and Sentencing in Chinese Criminal Justice: Problems and Solutions

  • Published:
Criminal Law Forum Aims and scope Submit manuscript

Abstract

The State Council of the People’s Republic of China has declared its intention to introduce AI into the Chinese criminal justice system including the imposition of criminal sentences. This plan has, however, raised a range of troubling questions and concerns which include the misinterpretation of court decisions by AI, the incapability of AI to make value judgements, possible biases of algorithms, selectivity of data used by AI, the “black box” character of sentencing by AI, diminished acceptance of AI-supported sentencing systems by the public, uncertain quality of algorithms, etc. The positive effect of AI on the goal of “same case, same sentence” therefore should not be overstated, and an unlimited application of AI must be avoided. Chinese policy makers should therefore use great caution when integrating AI into sentencing. AI should be employed not as a decision-maker but only as an “assistant”, providing information for judges and aiding them in making sentencing decisions. The final determination should in any event remain in the hands of the judges. Moreover, algorithms should be made transparent so that judges can review their operation. A Committee supervised by the Chinese Supreme Court should be established to guarantee the quality of judicial data used by AI and to operate a centralized AI system on sentencing. These measures would contribute to making the best use of judicial data and to introducing a fair, accurate, and efficient sentencing system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. A standard definition of AI does not yet exist. See Benedikt Kohn, KÜNSTLICHE INTELLIGENZ UND STRAFZUMESSUNG (Nomos 2020), p. 26. The core feature of AI is the ability to analyse input provided by humans and to produce outcomes for certain purposes. See Johannes Kaspar, Katrin Höffler, Stefan Harrendorf, “Datenbanken, Online-Votings und künstliche Intelligenz” (2020) 32 NEUE KRIMINALPOLITIK 35, 40; see also Stuart Russell and Peter Norvig, ARTIFICIAL INTELLIGENCE: A MODERN APPROACH (Pearson Global Edition 4th Edition 2021), pp. 19–20.

  2. According to empirical studies, algorithms based on big data are, on average, 10% more accurate than clinical predictions on human health and behaviour. William Grove, David Zald, Boyd Lebow, Beth Snitz, Chad Nelson, “Clinical Versus Mechanical Prediction: A Meta-Analysis” (2000) 12 PSYCHOL. ASSESSMENT 19, 19.

  3. Dan Hunter, Mirko Bagaric and Nigel Stobbs, “A Framework for the Efficient and Ethical Use of Artificial Intelligence in the Criminal Justice System” (2020) 47 FLA. ST. U. L. REV. 749, 752.

  4. The European Commission for the Efficiency of Justice, “Thematic Report: Use of Information Technology in European Courts” (2016), CEPEJ STUDIES No. 24, 22.

  5. Haibo Sun (孙海波), “Reflection on the Possibility and Limitation of Intelligent Judging (反思智能化裁判的可能及限度)” (2020) 5 REVIEW OF THE NATIONAL COLLEGE OF PROSECUTORS (国家检察官学院学报) 80, 81.

  6. Ibid.

  7. For two cases showing big disparities in Chinese sentencing see Julian V. Roberts and Wei Pei, “Structuring Judicial Discretion in China: Exploring the 2014 Sentencing Guidelines” (2016) 1 CRIMINAL LAW FORUM 27, 7.

  8. Chunyan Huang (黃春燕), “Sentencing Discretion of Judges and Realization of Sentencing Justice (法官量刑的自由裁量权与量刑公正的实现)” (2021) 296 JOURNAL OF SHANDONG NORMAL UNIVERSITY (SOCIAL SCIENCES) (山东师范大学学报(社会科学版))136, 136.

  9. Further examples can be found in: Roberts and Pei, supra note 7, 6.

  10. Tingguang Zhao (赵廷光), EMPIRICAL STUDY ON FAIRNESS OF SENTENCING (量刑公正实证研究) (Wuhan University Publishing 2005), p. 7.

  11. Yiwei Xia, Tianji Cai and Hua Zhong, “Effect of Judges’ Gender on Rape Sentencing” (2019) 19 THE CHINA REVIEW 125, 141.

  12. Neil Hutton, “Sentencing, Rationality, and Computer Technology” (1995) 22 J.L. & SOC’Y 549, 552.

  13. Huang (黃春燕), supra note 8, 137.

  14. 最高人民法院关于常见犯罪的量刑指导意见.法发[2013]14号 https://www.nmql.com/flvfgui/zyfgui/6853_5.html accessed 15/09/2021.

  15. See also Roberts and Pei, supra note 7, 3.

  16. Part III, Section 7 of the Guideline.

  17. 关于常见犯罪的量刑指导意见(二)(试行).法发[2017]7号 https://www.waizi.org.cn/doc/62824.html accessed 15 September 2021.

  18. 关于常见犯罪的量刑指导意见(试行).法发[2021]21号 https://www.chinalawtranslate.com/16861-2/ accessed 15/09/2021. These twenty-three crimes cover approximately 90% of all criminal cases. See https://www.sohu.com/a/476986647_114988 accessed 14/09/2021.

  19. For detailed rules issued by the Beijing High Court in 2014 see https://www.faxin.cn/lib/dffl/dfflcontent.aspx?gid=B1012559&nid=2650 accessed 14/09/2021.

  20. 国家信息化发展战略纲要 http://www.gov.cn/zhengce/2016-07/27/content_5095336.htm accessed 15/09/2021.

  21. 新一代人工智能发展规划, 国发[2017]35号 http://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm accessed 15/09/2021.

  22. 促进新一代人工智能产业发展三年行动计划(2018–2020年), 工信部科 [2017] 315号http://www.cac.gov.cn/2017-12/15/c_1122114520.htm accessed 15/09/2021.

  23. Weimin Zuo (左卫民), “How to Realize Similar Sentencing in Similar Cases with Artificial Intelligence (如何通过人工智能实现类案类判)” (2018) 20 CHINA LAW REVIEW (中国法律评论) 26, 27. This system is not applied nationwide.

  24. See Yadong Cui (崔亚东), ARTIFICIAL INTELLIGENCE AND MODERNIZATION OF THE JUDICIARY (人工智能与司法现代化) (Shanghai People Publishing 2019), pp. 111–6.

  25. Changshan Ma (马长山), “Reshaping Effect of Artificial Intelligence in Judiciary and its Limitation (司法人工智能的重塑效应及其限度)” (2020) 42 RESEARCH ON LAW (法学研究) 23, 28. Other AI systems in the judicial system are, for example, “Fawu Cloud” in Jiangsu Province, “Zhishen” in Hebei Province and “Fazhi Cloud” in Chongqing. Xi Zheng (郑曦), “Application and Regulation of Artificial Intelligence in Trials (人工智能技术在司法裁判中的运用及规制)” (2020) 32 PEKING UNIVERSITY LAW JOURNAL (中外法学) 674, 677.

  26. Homepage of “Little Judge Bao”: https://www.xiaobaogong.com.html accessed 14/09/2021.

  27. “Little Judge Bao” has already adapted its prediction system to the latest version of the Guidelines issued in July, 2021. See 关于常见犯罪的量刑指导意见 (试行), 法发(2021)21号 https://mp.weixin.qq.com/s/I-htMj42zpNoauoo4BwutQ accessed 14/09/2021.

  28. This table has been simplified by the author to only present the most important information. See https://mp.weixin.qq.com/s/I-htMj42zpNoauoo4BwutQ accessed 5/02/2022.

  29. There are two options for judges to choose: one is mitigation within the sentencing framework provided by CCL, the other is mitigation below the sentencing framework.

  30. See https://mp.weixin.qq.com/s/I-htMj42zpNoauoo4BwutQ accessed 14/09/2021.

  31. See https://mp.weixin.qq.com/s/UkEu_L4bedsHZArFGuDZpw accessed 14/09/2021. More information on this system can be found in an article published by its founder, Dr, Wang: Yanling Wang (王燕玲), “The Implementation and the Approach of Big Data Precise Sentencing (大数据精准量刑的实现方法与路径)” (2020) 38 JOURNAL OF GUIZHOU UNIVERSITY: SOCIAL SCIENCE (贵州大学学报(社会科学版)) 89, 97–100.

  32. Wenjie Feng (冯文杰), “Double-Construction of the Fairness of Artificial Intelligence in Sentencing (人工智能辅助量刑公正取向的双重构建)” (2020) 163 JOURNAL OF EAST CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY: SOCIAL SCIENCE (华东理工大学学报·社会科学版) 114, 119.

  33. Sarah Valentine, “Impoverished Algorithms: Misguided Governments, Flawed Technologies, and Social Control” (2019) 46 FORDHAM URBAN LAW JOURNAL 364, 365.

  34. Ma, supra note 25, 31.

  35. Huang (黃春燕), supra note 8, 143.

  36. Zheng, supra note 25, 678.

  37. (2017) Jin 01 Criminal Final No.41 ((2017) 津01刑终41号).

  38. The appeals court upheld the conviction but reduced the sentence to three years imprisonment with probation; (2017) Jin 01 Criminal Final No.41.

  39. Wenhua Peng (彭文华), “The History and Current Situation of the Federal Sentencing Guidelines and New Trends of Sentencing Reform in U.S. (美国联邦量刑指南的历史、现状与量刑改革新动向)” (2015) 6 JOURNAL OF COMPARATIVE LAW (比较法研究) 92, 104–5.

  40. Bensen Li (李本森), Three Points on Reform of Sentencing Standardization (量刑规范化改革的 ‘三点论’), in: Jinghai Shi (石经海) and Jinsong Lu (禄劲松) (ed) RESEARCH ON SENTENCING (量刑研究), Vol. 1 (Law Press China 2014), p. 7.

  41. Shaohua Zhou (周少华), “Like Cases Be Treated Alike: A Fictional Myth of the Rule of Law (同案同判:一个虚构的法治神话)” (2015) 11 LAW SCIENCE (法学)131, 140.

  42. Art. 61 CCL: “……the sentence shall be imposed on the basis of the facts of the crime, the nature and circumstances of the crime, and the degree of harm to society, in accordance with the relevant stipulations of this law.”

  43. Shizhou Wang (王世洲), “Modern Theories on the Purposes of Punishments and Chinese Choices (现代刑罚目的理论与中国的选择)” (2003) 3 RESEARCH ON LAW (法学研究) 107, 123.

  44. Sun, supra note 5, 89.

  45. Id 90.

  46. Guodong Zhang (张国栋), “Research on Application Limits of Artificial Intelligence in the Criminal Justice Field (人工智能在刑事裁判领域应用限度研究)” (2020) 113 JOURNAL OF BEIJING UNIVERSITY OF CHEMICAL TECHNOLOGY (SOCIAL SCIENCE EDITION) (北京化工大学学报(社会科学版)) 63,65.

  47. Arpan Mandal, Kripabandhu Ghosh, Saptarshi Ghosh and Sekhar Mandal, “Unsupervised Approaches for Measuring Textual Similarity between legal Court Case Reports” (2021) 29 ARTIF INTELL LAW 417, 418. See Jie Feng (冯洁), “Challenges of Artificial Intelligence to Theories on Trial: Response and Limitation (人工智能对司法裁判理论的挑战:回应及其限度)” (2018) 21 JOURNAL OF EASTERN CHINA UNIVERSITY OF POLITICAL SCIENCE AND LAW (华东政法大学学报) 21, 30.

  48. Lusheng Wang (王禄生), “Technological Obstacles of Judicial Big Data and the Development of Artificial Intelligence (司法大数据与人工智能开发的技术障碍)” (2018) 20 CHINA LAW REVIEW (中国法律评论) 46, 46.

  49. Zuo, supra note 23, 28.

  50. M Schwarze and JV Roberts, Reconciling Artificial and Human Intelligence, in: Jesper Ryberg and Julian V. Roberts (eds) SENTENCING AND ARTIFICIAL INTELLIGENCE, Oxford University Press 2022, p. 208.

  51. Andrea Roth, “Trial by Machine” (2016) 104 GEO. L.J. 1245, 1247.

  52. Jinghui Chen (陈景辉), “The Legal Challenges of Artificial Intelligence: What Is the Start? (人工智能的法律挑战:应该从哪里开始?)” (2018) 5 JOURNAL OF COMPARATIVE LAW (比较法研究), 136, 141.

  53. Sun, supra note 5, 95.

  54. Ibid.

  55. Zhao, (2017) Jin 01 Criminal Final No.41 (n 21).

  56. Ric Simmons, “Quantifying Criminal Procedure: How to Unlock the Potential of Big Data in Our Criminal Justice System” (2016) 4 MICH. ST. L. REV. 947, 980.

  57. Ibid. See also JD Humerick, “Reprogramming Fairness: Affirmative Action in Algorithmic Criminal Sentencing” (2019) 4 COLUM. HUM. RTS. L. REV. ONLINE 213, 244.

  58. Cui, supra note 24, 100. Inviting private companies to develop AI for the judicial system has been supported by the President of the Chinese Supreme Court. Zheng, supra note 25, 683.

  59. Zheng, supra note 25, 683.

  60. Simmons, supra note 56, 970.

  61. Zheng, supra note 25, 684.

  62. Huang, supra note 8, 138.

  63. Anne von der Lieth Gardner, AN ARTIFICIAL INTELLIGENCE APPROACH TO LEGAL REASONING (MIT Press 1987), pp. 59–60.

  64. Homepage https://wenshu.court.gov.cn/ accessed 21/03/2022.

  65. See https://www.bjcourt.gov.cn/article/newsDetail.htm?NId=175002668&channel=100001012 accessed 21/03/2022.

  66. See https://wenshu.court.gov.cn/website/wenshu/181217BMTKHNT2W0/index.html?pageId=01f6fd40936e5b4c366ec5e7d671eef6&s8=02 accessed 21/03/2022. This number includes decisions in all instances and rulings on procedural issues.

  67. Weimin Zuo (左卫民), “Towards Legal Research with Big Data (迈向大数据法律研究” (2018) 40 CHINESE JOURNAL OF LAW (法学研究)139, 142.

  68. However, the Beijing High Court claims that it publishes 99.9% of those cases which can be published. See https://www.bjcourt.gov.cn/article/newsDetail.htm?NId=175002668&channel=100001012 accessed 21/03/2022.

  69. Working report for 2020 issued by Beijing High Court: https://www.bjcourt.gov.cn/article/newsDetail.htm?NId=175002668&channel=100001012 accessed 21/03/2022.

  70. https://wenshu.court.gov.cn/website/wenshu/181217BMTKHNT2W0/index.html?pageId=01f6fd40936e5b4c366ec5e7d671eef6&s8=02 accessed 21/03/2022.

  71. https://www.thepaper.cn/newsDetail_forward_11028621 accessed 21/03/2022.

  72. https://wenshu.court.gov.cn/website/wenshu/181217BMTKHNT2W0/index.html?pageId=01f6fd40936e5b4c366ec5e7d671eef6&s8=02 accessed 21/03/2022.

  73. Para. 2 of Art. 1 of Interpretation of the Supreme People’s Court and the Supreme People’s Procuratorate on Several Issues concerning the Application of Law in the Handling of Criminal Cases of Theft (最高人民法院、最高人民检察院关于办理盗窃刑事案件适用法律若干问题的解释) provides: “The higher people’s courts and the people’s procuratorates of all provinces, autonomous regions and municipalities directly under the Central Government may, in light of the economic development status of their respective regions, and in consideration of the social security situation, determine, within the scope of the amounts specified in the preceding paragraph, specific amount standards for their respective regions, and report them to the Supreme People’s Court and the Supreme People’s Procuratorate for approval.” A list of incriminating thresholds for theft in different Chinese provinces can be found: http://www.gztingjun.com/m/view.php?aid=615 accessed 14/09/2021.

  74. Para. 1, No.4 of the Guidelines provides that judges should consider the economic situation and the imposed sentences for similar cases in their area. This means that sentencing for similar cases in different areas can differ.

  75. Zuo, supra note 23, 28–9.

  76. Notice on Special Combat against Criminal Clan (关于开展扫黑除恶专项斗争的通知) http://www.gov.cn/zhengce/2018-01/24/content_5260130.htm accessed 14/09/2021.

  77. Zhang, supra note 46, 66.

  78. Weimin Zuo (左卫民), “Several Considerations on Prospect of the Application of Legal Artificial Intelligence in China (关于法律人工智能在中国运用前景的若干思考)” (2018) 12 TSINGHUA LAW REVIEW (清华法学)108, 114–7. See also Zheng, supra note 25, 679.

  79. Zuoxiang Liu (刘作翔), “Criticism on Local Protectionism in Chinese Judiciary (中国司法地方保护主义之批判)” (2003) 1 RESEARCH ON LAW (法学研究) 83, 90–4.

  80. Zhang, supra note 46, 67.

  81. Id 66.

  82. Xi Si (司旭) and Jin Wang (王进), “Research on Reasoning on Sentencing in Criminal Decisions (我国刑事判决书量刑说理问题研究)” (2018) 159 JOURNAL OF SHANDONG ACADEMY OF GOVERNANCE (山东行政学院学报) 76, 78.

  83. Yueqin Jiao (焦悦勤), “Survey on Reasoning on Sentencing and Research on the Reform Approach (刑事判决书量刑说理现状调查及改革路径研究) (2016) 34 HEBEI LAW (河北法学) 75, 79.

  84. Id 77. However, the author did not explain his standards on determining “sufficient reasoning” or “insufficient reasoning”.

  85. Jiahui Shi (石家慧), “Reconsideration of the Role of Prosecutors in the Chinese Plea Bargaining System: A Comparative Perspective” (2021) 10 CHINESE STUDIES 88, 90.

  86. Yunteng Hu (胡云腾), INTERPRETATION AND APPLICATION OF CHINESE PLEA BARGAINING (认罪认罚从宽制度的理解与适用) (People’s Court Press 2018), pp. 271–8.

  87. Zhaokun Shi (史兆琨), “Several Indexes on Procedural Supervision increase to Provide Legal Protection (多项诉讼监督指标“止降转升”, 努力为大局稳定提供法治保障)”, Daily of Prosecution (檢察日報) (Beijing, 24/07/2020) https://news.sina.com.cn/c/2020-07-24/doc-iivhuipn4773042.shtml accessed 14/09/2021.

  88. For example, (2021) Liao 0682 Criminal First Instance No. 188 ((2021) 辽0682刑初188号).

  89. For example, (2021) Liao 0106 Criminal First Instance No. 619 ((2021) 辽0106刑初619号).

  90. Zhang, supra note 46, 66.

  91. Jiahui Shi (石家慧), “Self-defence in German Criminal Law (德国刑法中的正当防卫制度)” (2018) 6 CHINA REVIEW OF ADMINISTRATION OF JUSTICE (中国应用法学) 173,173.

  92. Ric Simmons, “Big Data and Procedural Justice: Legitimizing Algorithms in the Criminal Justice System” (2018) 15 OHIO ST. J. CRIM. L. 573, 573.

  93. Id 574.

  94. Tom R. Tyler, WHY PEOPLE OBEY THE LAW (Princeton University Press 1990), p. 109.

  95. Simmons, supra note 92, 579–80.

  96. Ric Simmons, “Big Data, Machine Judges, and the Legitimacy of the Criminal Justice System” (2018) 52 UNIVERSITY OF CALIFORNIA DAVIS LAW REVIEW 1067, 1087.

  97. Section 4 of Decisions on Several Important Issues on Promoting Rule of Law(中共中央关于全面推进依法治国若干重大问题的决定) mentions that “……try to make the public feel fairness and justice in every case”. http://www.gov.cn/zhengce/2014-10/28/content_2771946.htm accessed 14/09/2021. For a similar opinion see Tyler (n 94) 107, stating that “fair procedures can act as a cushion of support when authorities are delivering unfavorable outcomes.”

  98. See https://www.chinacourt.org/article/detail/2016/11/id/2336215.shtml accessed 14/09/2021.

  99. Some authors argue that live-streaming of trials has a negative effect on truth-finding. Weimin Zuo (左卫民), “Rethinking Live-stream of Trials: From the Perspective of Judicial Transparency (反思庭审直播 – 以司法公开为视角)” (2020) 9 POLITICAL SCIENCE AND LAW (政治与法律) 91, 98.

  100. Johannes Kaspar, Katrin Höffler, Stefan Harrendorf, “Datenbanken, Online-Votings und künstliche Intelligenz” (2020) 32 NEUE KRIMINALPOLITIK 35, 51–2.

  101. See, e.g., E. Allan Lind, Ruth Kanfer, P. Christopher Earley, “Voice, Control, and Procedural Justice: Instrumental and Noninstrumental Concerns in Fairness Judgements” (1990) 59 J. PERSONALITY & SOC. PSYCHOL. 952.

  102. Yujie Zhang (张玉洁), “Judicial Application on Sentencing Algorithms: Logic, Difficulties and Procedure Responses (智能量刑算法的司法适用: 逻辑、难题与程序法回应)” (2021) 3 ORIENTAL LAW (东方法学) 187, 194.

  103. Zheng, supra note 25, 678.

  104. Weidong Ji (季卫东), “Changes of Judicial Power in AI Era (人工智能时代的司法权之变)” (2018) 1 ORIENTAL LAW (东方法学) 125,132.

  105. Hang Zhen (甄航), “Artificial intelligence intervention in sentencing mechanism: dilemma, orientation and deconstruction (人工智能介入量刑机制:困境、定位与解构), JOURNAL OF CHONGQING UNIVERSITY (SOCIAL SCIENCE EDITION) (重庆大学学报(社会科学版)) (first published online 18/12/2020). https://doi.org/10.11835/j.issn.1008-5831.fx.2020.12.003. The author argued that AI should “regulate” the behavior of judges which means that judges must give explanations when they do not want to follow the outcome offered by AI.

  106. Roth, supra note 51, 1247.

  107. Simmons, supra note 96, 1096.

  108. Lee Rainie and Janna Anderson, Code-Dependent: Pros and Cons of the Algorithm Age, Pew Res. Ctr. (Feb. 8, 2017) https://www.pewresearch.org/internet/2017/02/08/code-dependent-pros-and-cons-of-the-algorithm-age/ accessed 14/09/2021.

  109. Stephen E. Henderson, “A Few Criminal Justice Big Data Rules” (2018) 15 OHIO ST. J. CRIM. L. 527, 534.

  110. See Grove, supra note 2, 19.

  111. 最高人民法院关于加强和规范裁判文书释法说理的指导意见, 法发[2018]10号 http://www.court.gov.cn/zixun-xiangqing-101552.html accessed 15/09/2021.

  112. Some courts reward judges if their decisions are selected by the Supreme Court as “Model Cases”.

  113. The current version of the Judge Law of the P.R. China (中华人民共和国法官法) does not contain any obligation to give reasons for judgments.

  114. These marked decisions, including the decisions applying the law incorrectly, should still remain in the database “Chinese Judgements Online”. Although they have little value for AI they could still be used for other purposes, such as academic research and public supervision.

  115. Jason Tashea, “Calculating Crime” (2017) 103-MAR A.B.A. J. 54, 58.

  116. Simmons, supra note 96,1087.

  117. See Lind et al., supra note 101.

  118. Hunter, supra note 3, 785.

  119. Sun, supra note 5, 89.

  120. Mandal et al., supra note 47, 418.

  121. https://advancingpretrial.org/psa/about/ accessed 14/09/2021. The PSA was developed by Arnold Ventures and more than 40 jurisdictions across the country have implemented the tool. See https://www.nmcourts.gov/court-administration/pretrial-release-and-detention-reform/public-safety-assessment-for-pretrial-release-and-detention/ accessed 14/09/2021.

  122. https://advancingpretrial.org/psa/factors/ accessed 14/09/2021.

  123. Simmons, supra note 56, 965–6.

  124. https://advancingpretrial.org/psa/about/ accessed 14/09/2021.

  125. Even the system developed by the Chinese Supreme Court used to refer to “same cases” is not a centralized one and has not been adopted by every court.

  126. Zuo, supra note 23, 28–9.

  127. Rainie and Anderson, supra note 108, accessed 14/09/2021.

  128. Kia Rahnama, “Science and Ethics of Algorithms in the Courtroom” (2019) 2 JOURNAL OF LAW, TECHNOLOGY AND POLICY 169, 186.

  129. Ibid. See also Mike Ananny, “Toward an Ethics of Algorithms: Convening, Observation, Probability, and Timeliness” (2016) 41 SCI. TECH. & HUM. VALUES 93, 96.

Acknowledgements

I would like to express my special thanks to Prof. Dr. Thomas Weigend at the University of Cologne for encouraging me to initiate this project and for offering valuable comments and feedback on this manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jiahui Shi.

Ethics declarations

Conflict of interest

I have no conflict of interest to disclose.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Shi, Jiahui is a research assistant at the Law Faculty, Sichuan University, China. She received her doctorate in law (Dr. iur.) from the University of Cologne, Germany, and Bachelor and Master of Law Degrees from the China University of Political Science and Law, Beijing. Her research areas cover criminal law, criminal procedure law, comparative law, technological law, and law on privacy.

Dr. iur., University of Cologne (Germany); research assistant, Law Faculty, Sichuan University, China. E-mail: shijiahui2006zxl@gmail.com

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shi, J. Artificial Intelligence, Algorithms and Sentencing in Chinese Criminal Justice: Problems and Solutions. Crim Law Forum 33, 121–148 (2022). https://doi.org/10.1007/s10609-022-09437-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10609-022-09437-5

Navigation