人工智能与中国司法审判的智能化
Introduction / 1
Chapter 1 Status Quo of Trial Efficiency and Quality in China’s Civil Litigation / 13
1.1 Status Quo of Trial Efficiency and Quality in China / 14
1.1.1 Evaluation of Trial Efficiency / 15
1.1.2 Evaluation Index of Trial Quality of Courts in China / 18
1.2 Weights Setting of Judges’ Performance Assessment Indicators / 25
1.3 Insufficient Trial Resources in Local Courts / 29
1.3.1 Dramatically Increased Cases but Limited Quota Judges / 30
1.3.2 Great Pressure on Judges / 33
1.3.3 AI Making Up for the Shortage of Judicial Assistants / 36
1.4 Loopholes of Internal Trial Supervision Brought by Judicial Accountability System / 38
1.4.1 Court Leading Cadres Being Hesitant or Unwilling to Supervise / 41
1.4.2 Defects of the New Case Assignment System / 43
1.4.3 Other Dilemmas / 46
1.5 Trial-quality Ignorance of the Smart Court Construction in the Early Stage / 49
1.5.1 Construction and Development History of Smart Courts / 52
1.5.2 Applications of Artificial Intelligence in Smart Courts / 56
1.5.3 The Goal Pursuit in the Early Stage of Smart Courts: Efficiency Orientation / 81
1.6 Distrust on AI Participating in Trial: Based on a Questionnaire / 85
1.6.1 Overview Information of Respondents and Investigation Methodology of the Questionnaire / 86
1.6.2 Survey Results and Data Analysis / 88
1.7 Conclusion / 96
Chapter 2 Legal Reasoning and the Development of Court Intelligent Auxiliary Case Handling System / 98
2.1 Development Goal: Promoting Trial Quality and Further Improving Trial Efficiency / 102
2.1.1 General Goal of Trial Quality: Treating Similar Cases Alike / 102
2.1.2 Sub-goal 1: to Solve the Law Application Justification Problems / 105
2.1.3 Sub-goal 2: to Solve the Problem of Unifying“ Similar Cases” Standard / 109
2.1.4 Sub-goal 3: to Solve the Problem in the Legal Reasoning Process / 115
2.1.5 Other Sub-goals / 118
2.2 Selection of Research and Development Domain / 119
2.3 Jurisprudence Basis and Model of Legal Reasoning / 126
2.3.1 Deduction: Rule-Based Reasoning / 127
2.3.2 Non-monotonic Logic and Defeasible Reasoning Model / 129
2.3.3 Analogy: Case-Based Reasoning and Knowledge-Based Reasoning / 137
2.3.4 Cooperative Paradigm Reasoning Model— Chinese Choice / 144
2.4 Building the Intelligent Auxiliary Case Handling System for Road Traffic Accident Compensation Disputes / 147
2.4.1 Building Rule-Based Reasoning System / 148
2.4.2 Building Knowledge-Based Reasoning Model / 155
2.4.3 Establishment of Defeasible Reasoning Model / 164
2.4.4 Construction of Case-Based Reasoning Model / 167
2.4.5 Establishment of Intelligent Auxiliary Case Handling System / 178
2.5 Conclusion / 183
Chapter 3 Law Expectation and Due Process: From Perspective of Civil Litigation / 188
3.1 Absence of Law Causing Legal Expectation of Intelligent Trial Failed / 189
3.2 Embedding the Intelligent Auxiliary Case Handling System in Civil Procedure / 194
3.2.1 Element-Oriented Trial Mode Applied in Road Traffic Cases / 194
3.2.2 Scope of the Element-Oriented Court Trial Expanded to Complicated Cases / 208
3.2.3 Different Judgment Reasoning Requirements in Summary and
Formal Procedures / 213
3.2.4 Embedding the Intelligent Auxiliary Case Handling System in Civil Procedures / 217
3.3 Institutional Design of Intelligent Adjudication in the Civil Procedure Law / 220
3.3.1 Substituting the Judge to Make Adjudication in Summary Procedure / 221
3.3.2 Assisting the Judge to Make Adjudication in Formal Procedure / 223
3.3.3 Compulsory Application of the IACHS in the First Instance Trial in the
Selected Domain / 227
3.3.4 Trial Responsibility Allocation / 235
3.3.5 Application of IACHS in Appeal and Retrial Procedure / 240
3.4 Dual Shaping of Due Process on the IACHS: Procedural Legitimacy and
Substantive Legitimacy / 243
3.4.1 Procedure Subjects: Role Separation / 246
3.4.2 Subject’s Behavior: Time Requirements and Communication Rules / 250
3.4.3 Procedure Result: Judgment Acceptability / 260
3.5 Conclusion / 263
Findings and Forward: the Judicial World of Human-Machine Collaboration / 267
Appendix 1 / 285
Appendix 2 / 288
Appendix 3 / 292
Chapter 1 Status Quo of Trial Efficiency and Quality in China’s Civil Litigation / 13
1.1 Status Quo of Trial Efficiency and Quality in China / 14
1.1.1 Evaluation of Trial Efficiency / 15
1.1.2 Evaluation Index of Trial Quality of Courts in China / 18
1.2 Weights Setting of Judges’ Performance Assessment Indicators / 25
1.3 Insufficient Trial Resources in Local Courts / 29
1.3.1 Dramatically Increased Cases but Limited Quota Judges / 30
1.3.2 Great Pressure on Judges / 33
1.3.3 AI Making Up for the Shortage of Judicial Assistants / 36
1.4 Loopholes of Internal Trial Supervision Brought by Judicial Accountability System / 38
1.4.1 Court Leading Cadres Being Hesitant or Unwilling to Supervise / 41
1.4.2 Defects of the New Case Assignment System / 43
1.4.3 Other Dilemmas / 46
1.5 Trial-quality Ignorance of the Smart Court Construction in the Early Stage / 49
1.5.1 Construction and Development History of Smart Courts / 52
1.5.2 Applications of Artificial Intelligence in Smart Courts / 56
1.5.3 The Goal Pursuit in the Early Stage of Smart Courts: Efficiency Orientation / 81
1.6 Distrust on AI Participating in Trial: Based on a Questionnaire / 85
1.6.1 Overview Information of Respondents and Investigation Methodology of the Questionnaire / 86
1.6.2 Survey Results and Data Analysis / 88
1.7 Conclusion / 96
Chapter 2 Legal Reasoning and the Development of Court Intelligent Auxiliary Case Handling System / 98
2.1 Development Goal: Promoting Trial Quality and Further Improving Trial Efficiency / 102
2.1.1 General Goal of Trial Quality: Treating Similar Cases Alike / 102
2.1.2 Sub-goal 1: to Solve the Law Application Justification Problems / 105
2.1.3 Sub-goal 2: to Solve the Problem of Unifying“ Similar Cases” Standard / 109
2.1.4 Sub-goal 3: to Solve the Problem in the Legal Reasoning Process / 115
2.1.5 Other Sub-goals / 118
2.2 Selection of Research and Development Domain / 119
2.3 Jurisprudence Basis and Model of Legal Reasoning / 126
2.3.1 Deduction: Rule-Based Reasoning / 127
2.3.2 Non-monotonic Logic and Defeasible Reasoning Model / 129
2.3.3 Analogy: Case-Based Reasoning and Knowledge-Based Reasoning / 137
2.3.4 Cooperative Paradigm Reasoning Model— Chinese Choice / 144
2.4 Building the Intelligent Auxiliary Case Handling System for Road Traffic Accident Compensation Disputes / 147
2.4.1 Building Rule-Based Reasoning System / 148
2.4.2 Building Knowledge-Based Reasoning Model / 155
2.4.3 Establishment of Defeasible Reasoning Model / 164
2.4.4 Construction of Case-Based Reasoning Model / 167
2.4.5 Establishment of Intelligent Auxiliary Case Handling System / 178
2.5 Conclusion / 183
Chapter 3 Law Expectation and Due Process: From Perspective of Civil Litigation / 188
3.1 Absence of Law Causing Legal Expectation of Intelligent Trial Failed / 189
3.2 Embedding the Intelligent Auxiliary Case Handling System in Civil Procedure / 194
3.2.1 Element-Oriented Trial Mode Applied in Road Traffic Cases / 194
3.2.2 Scope of the Element-Oriented Court Trial Expanded to Complicated Cases / 208
3.2.3 Different Judgment Reasoning Requirements in Summary and
Formal Procedures / 213
3.2.4 Embedding the Intelligent Auxiliary Case Handling System in Civil Procedures / 217
3.3 Institutional Design of Intelligent Adjudication in the Civil Procedure Law / 220
3.3.1 Substituting the Judge to Make Adjudication in Summary Procedure / 221
3.3.2 Assisting the Judge to Make Adjudication in Formal Procedure / 223
3.3.3 Compulsory Application of the IACHS in the First Instance Trial in the
Selected Domain / 227
3.3.4 Trial Responsibility Allocation / 235
3.3.5 Application of IACHS in Appeal and Retrial Procedure / 240
3.4 Dual Shaping of Due Process on the IACHS: Procedural Legitimacy and
Substantive Legitimacy / 243
3.4.1 Procedure Subjects: Role Separation / 246
3.4.2 Subject’s Behavior: Time Requirements and Communication Rules / 250
3.4.3 Procedure Result: Judgment Acceptability / 260
3.5 Conclusion / 263
Findings and Forward: the Judicial World of Human-Machine Collaboration / 267
Appendix 1 / 285
Appendix 2 / 288
Appendix 3 / 292
张娟娟，法学博士，西南科技大学法学院讲师，在墨西哥科利马大学做过访问学者，本科、硕士、博士分别毕业于天津大学、西南政法大学和澳门大学。从事国际法和人工智能法学方向研究，主持和参与省部级、地厅级项目若干项，公开发表期刊论文20余篇。
本书是我国人工智能与法学跨学科研究领域一次新的尝试，通过大量实证分析，包括问卷调查、数据分析以及专家访谈等形式，分析了影响司法审判质量和效率的主要因素，论证现阶段人工智在辅助法官进行案件处理，包括法律推理、规则论证、相似案例检索、类案分析等方面的可行性，为审判质量和效率的提升提供了解决的新思路，可作为我国高校学者以及法院相关从业人员研究人工智能和法律结合提供参考。
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