The Use of Artificial Intelligence in the Public Sector in Shanghai : Ambition, Capacity and Reality

This book examines how Shanghai aims to improve public service provision by accelerating the use of artificial intelligence (AI) in the public sector. After clarifying the technical and social factors that shape the use of AI in this area, the book delves into the AI policy environment and AI ecosystem of Shanghai to gauge the city’s capacity to implement public sector AI applications. Then it examines how this capacity translates into real-world policy initiatives through the investigation of case studies. It highlights the analytical, operational and political capabilities that determine the strengths and limitations of such initiatives in deploying AI in the public sector, and it assesses their impacts on public service provision in Shanghai. By using the findings on Shanghai to gain a deeper understanding of key topics in public sector AI research, this book also contributes new knowledge about the use of AI to improve the provision of public services. Acknowledgments Contents Acronyms, Abbreviations, and Currencies List of Figures List of Boxes List of Tables 1 Approaching China’s “Artificial Intelligence Development Highland” References 2 Artificial Intelligence in the Public Sector in Shanghai: Conceptualization, Context, and Capacity 2.1 Conceptualizing AI in the Public Sector 2.1.1 Research Approaches of Previous Studies on AI in the Public Sector 2.1.2 Public Sector AI Research: Toward an Integrated Framework 2.2 Mapping the Field: Artificial Intelligence in the Public Sector in China 2.2.1 Artificial Intelligence Systems Conceptual View of AI Systems Systematizing AI-related Terminology 2.2.2 AI in the Public Sector: Activities, Drivers, and Barriers AI in the Public Sector: Classes of Activities Drivers: Benefits of Using AI in the Public Sector Barriers: Challenges of Using AI in the Public Sector 2.2.3 Factors Affecting the Use of AI in the Public Sector in China Mobilizing Local Governments: the Evaluation System for Promotion Engaging AI Companies: The State as a Partner National New Generation Artificial Intelligence Open Innovation Platforms (AIOIPs) The Artificial Intelligence Industry Alliance (AIIA) Chinese Initiatives in AI Regulation and AI Ethics Chinese Initiatives in AI Regulation Chinese Initiatives in AI Ethics Defining “AI in the Public Sector in China” 2.3 Using AI in the Public Sector in Shanghai: The Policy Capacity Framework 2.3.1 Assessing Policy Capacity 2.3.2 Assessing Shanghai’s Policy Capacity to Use AI in the Public Sector 2.4 Implications for Studying AI in the Public Sector in Shanghai Appendix I: Chinese-Language Public Sector AI Research Appendix II: Main Contents of Chinese AI Ethics Principles References 3 The AI Policy Environment of Shanghai 3.1 China’s AI Strategy: The New Generation Artificial Intelligence Development Plan 3.1.1 The Goals of the AIDP: Technology, Economy, Society, and Security 3.1.2 AI in the Public Sector: Build an Intelligent Society 3.1.3 The AIDP: Implications for the Study of Shanghai’s AI Plans 3.2 The Municipal Plans for AI Development in Shanghai 3.2.1 The Opinions on Promoting a New Generation AI in Shanghai 3.2.2 Action Plan for Building Shanghai into an AI Highland (2019–2021) 3.2.3 Goals and Actions: Substantiating the AI Plans of Shanghai Shanghai Data Innovation Center The AI Pilot Application Scenarios Digital Initiatives for Public Sector Innovation 3.3 Main Findings Appendix III: Toward China’s National AI Strategy (2015–2016) Appendix IV: Main National AI Policy Documents published After the AIDP References 4 The AI Ecosystem of Shanghai 4.1 Access and Use of Data 4.1.1 Data Metrics for Shanghai 4.1.2 Public Data Sharing 4.1.3 Data Privacy Regulations 4.1.4 Conclusions on the Data Indicator 4.2 Technological and Physical Infrastructure 4.2.1 Physical Infrastructure 4.2.2 Technological Infrastructure 4.2.3 Conclusions on the Infrastructure Indicator 4.3 AI Talents 4.3.1 The AI Talent Pool of Shanghai 4.3.2 Shanghai’s AI Talent Outputs 4.3.3 Shanghai’s AI Talent Inputs 4.3.4 Conclusions on the AI Talent Indicator 4.4 AI Companies 4.4.1 AI Companies in Shanghai 4.4.2 Supporting and Engaging AI Companies 4.4.3 Conclusions on the AI Company Indicator 4.5 Social Acceptance 4.5.1 Surveys on Public Perception of AI in China 4.5.2 Conclusions on the Social Acceptance Indicator 4.6 Main Findings References 5 Public Sector AI Applications in Shanghai 5.1 Capacity in Action: The Strategy of Shanghai for AI in the Public Sector 5.1.1 Analytical Capacity in Action 5.1.2 Political Capacity in Action 5.1.3 Operational Capacity in Action 5.1.4 Outlining Shanghai’s Policy Strategy for AI in the Public Sector 5.2 The Platform-Based Approach: “One City, Two Networks” 5.2.1 The Government Online-Offline Shanghai Project Description Strengths and Limitations in Deploying AI in the Public Sector Implications of the Government Online-Offline Shanghai for Public Service Provision 5.2.2 The Single Platform for Urban Management Project Description Strengths and Limitations in Deploying AI in the Public Sector Implications of the Single Platform for Urban Management for Public Service Provision 5.2.3 Conclusions on the Platform-Based Approach 5.3 Experiment-Based Approach: The AI Pilot Application Scenarios 5.3.1 Project Description An Overview of the AI Pilot Application Scenarios 5.3.2 Strengths and Limitations of the AI Pilots in Deploying AI in the Public Sector Organizational Experiments Under Municipal Lead Deregulated Approach to AI Innovation Engagement of Private AI Companies 5.3.3 Implications of the AI Pilots for Public Service Provision 5.4 Main Findings from Public Sector AI Applications in Shanghai 5.4.1 Shanghai’s Strategy for AI in the Public Sector: Comparing the Approaches Coordination Systematization Proactivity 5.4.2 Shanghai’s Strategy for AI in the Public Sector: Comparing the Impacts Appendix V: Interview Sample Questions Appendix VI: AI Pilot Application Scenarios—Case Studies Case Study 1: Minhang Qiangwei Primary School (闵行蔷薇小学) Case Study 2: Shanghai Shixi High School (上海市市西中学) Case Study 3: Shanghai World Foreign Language Education Group (WFL, 上海世外教育集团) Case Study 4: Luwan No. 1 Central Primary School (卢湾一中心小学) Case Study 5: Shanghai No. 10 People’s Hospital (上海市第十人民医院) Case Study 6: Fudan University Shanghai Cancer Hospital (复旦大学附属肿瘤医院) Case Study 7: Shanghai Children’s Medical Center, Eastern Medical Complex (Pudong and Fengxian Districts) (上海儿童医学中心东部儿科医疗联合体 (浦东新区、奉贤区)) Case Study 8: Shanghai Ruijin Hospital (上海交通大学医学院附属瑞金医院) Case Study 9: Changning District Beixinjing Subdistrict (长宁区北新泾街道) Case Study 10: Xuhui District Xietu Road Subdistrict (徐汇区斜土路街道) Case Study 11: Zhangjiang Artificial Intelligence Island (张江人工智能岛) Case Study 12: Shanghai Lingang Intelligent Connected Vehicles Comprehensive Demonstration Zone (上海临港智能网联汽车综合测试示范区) Case Study 13: Shanghai Subway (上海地铁集团) Case Study 14: Jing’an Government Data Management Center (静安政务数据管理中心) Case Study 15: The Shanghai Museum (上海博物馆) Case Study 16: Shanghai Financial Court (上海金融法院) References 6 Ambition, Capacity, Reality, Insights, and Prospects 6.1 Insights and Prospects from China’s “AI Highland” 6.1.1 Setting Policy Goals for AI in the Public Sector 6.1.2 Cooperating with Private Companies in Public Sector AI Projects 6.1.3 Managing the Ethical Challenges of AI in the Public Sector 6.2 What’s Next? AI in the Urban Digital Transformation of Shanghai 6.3 A Window on the Future References Glossary Bibliography Index