AI and the Future of the Public Sector: The Creation of Public Sector 4.0

Cover
Title Page
Copyright Page
Contents
Acknowledgments
About the Author
Introduction
The Political Perspective
Notes
Chapter 1 Understanding the Key Building Blocks of Progress
1.1 Introduction
1.2 Key Building Blocks of Data Science and AI
1.2.1 Data Acquisition
1.2.2 Data Maintenance
1.2.3 Analysis
1.2.4 Communication
1.2.5 Machine Learning
1.2.6 Artificial Intelligence
1.2.7 Advantages and Disadvantages
1.2.8 Four Key Focuses for Future AI
1.3 Quantum Computing
1.3.1 What Is Quantum Computing?
1.3.2 Impact on Cybersecurity
1.4 Proliferation of Devices
1.5 5G and the Impact of Advanced Communications
1.5.1 Global Transformation
1.6 Public Sectors 4.0
1.7 Conclusion
1.8 Notes
Chapter 2 Office of Finance
2.1 Introduction
2.2 Forecasting and Public Finance Management
2.3 Forecasting
2.3.1 Qualitative Forecasting
2.3.2 Quantitative Forecasting
2.3.3 Forecasting for Public Sector Transformation
2.3.4 Managing Risk and Uncertainty
2.3.5 Forecasting in IT Projects
2.3.6 The Move Toward Activity-Based Costing
2.3.7 Hard Benefits and Soft Benefits
2.3.8 Enterprise Resource Planning
2.3.9 AI and Governmental Administration
2.3.10 Global Partnership on AI
2.4 Conclusion
2.5 Notes
Chapter 3 Public Order and Safety
3.1 Introduction
3.2 The Future of Policing in an AI Era
3.2.1 Transformation of Police Work
3.2.2 Criminal Use of AI
3.2.3 Police Use of New Technologies
3.2.4 Case Studies in Policing
3.2.5 Policing in China
3.2.6 Forward-Looking Policing
3.3 AI in Policing
3.3.1 Impact on Police Behavior
3.4 The Citizen as a Key Component of Future Policing
3.5 Police and Location Analytics
3.6 Policing Summary
3.7 Border Security and AI
3.8 Customs Reform
3.8.1 The Citizen and Taxation
3.9 Fire Safety and AI
3.9.1 Natural Fire Prevention
3.9.2 Prevention of Urban Fires
3.9.3 Smart Homes and Fire Detection
3.9.4 Commercial Fire Prevention
3.9.5 Firefighting Using AI
3.9.6 Fire Station Locations
3.10 Conclusion
3.11 Notes
Chapter 4 Personal Social Services
4.1 Introduction
4.2 Care Homes
4.2.1 The UK Model
4.2.2 Care Homes in Japan
4.2.3 The Canadian Picture
4.2.4 The Emergence of AgeTech
4.2.5 Going Forward
4.2.6 Conclusion
4.3 Impact on Children
4.4 Mental Health
4.5 Social Protection
4.5.1 Social Risk Framework
4.6 Employment and Benefit Management
4.7 Conclusion
4.8 Notes
Chapter 5 Health
5.1 Introduction
5.2 Digitalization and Its Importance in Healthcare
5.2.1 Different Categories of Data Sources in Healthcare
5.3 Medical Monitoring and Biosensors
5.3.1 Use of Biosensors in Mental Health
5.4 Innovating to Zero in Healthcare
5.4.1 Zero Invasive Surgery
5.4.2 Zero Waste Management
5.4.3 Zero Surgical Errors
5.5 Tissue Engineering
5.6 Cybernetics
5.7 Advancements in Drug Creation and Treatment
5.8 Case Studies in Healthcare
5.8.1 Ping An Good Doctor
5.8.2 Cancer Screening Case Study
5.9 Paramedics and AI
5.10 Cybersecurity in Healthcare
5.11 Conclusion
5.12 Notes
Chapter 6 Education
6.1 Introduction
6.2 Learning for the Future
6.3 Teaching in the Future
6.3.1 The Use of AI for Predicting Exam Success
6.4 AI and Language in the Classroom
6.4.1 Automated Essay Scoring
6.4.2 Removing Communication Barriers
6.5 Robots in the Classroom
6.6 The Shortage of Tech Talent
6.7 Case Studies in Education
6.8 Conclusion
6.9 Notes
Chapter 7 Defense
7.1 Introduction
7.2 Use Cases of AI in Defense
7.2.1 Intelligence, Surveillance, and Reconnaissance
7.2.2 Logistics
7.2.3 Cyberspace Operations
7.2.4 Information Operations and “Deep Fakes”
7.2.5 Command and Control
7.2.6 AI and Augmented Reality Soldiers
7.2.7 Semi-Autonomous and Autonomous Vehicles
7.3 Ethical Issues
7.4 Drones
7.5 Conclusion
7.6 Notes
Chapter 8 Smarter Cities and Transportation
8.1 Introduction
8.2 Smarter Cities
8.2.1 Smart Infrastructure
8.2.2 Smart Transportation
8.2.3 Street Lighting
8.2.4 Water Utilities
8.2.5 Emergency Services
8.2.6 Waste Collection and Disposal
8.2.7 Maintenance of Public Places
8.2.8 Humans as Devices
8.2.9 Data Challenges for Smart Cities
8.3 Transportation
8.3.1 Traffic Management
8.3.2 Road Safety
8.3.3 Highway Maintenance
8.3.4 Autonomous Trams
8.3.5 Autonomous Taxis
8.4 Railways and the Future of Rail
8.4.1 Net Zero in Rail
8.4.2 AI and Effective Rail Timetabling
8.5 Air Travel
8.6 Conclusion
8.7 Notes
Chapter 9 Housing and the Environment
9.1 Introduction
9.2 AI in Social Housing
9.2.1 Risk Management in Social Housing
9.2.2 Transforming the Tenant Experience
9.2.3 Case Study – Housemark Pilot
9.2.4 Social Housing Fraud
9.2.5 Tenant Viewpoint
9.2.6 AI as a Virtual Housing Assistant
9.2.7 Chatbots in Social Housing
9.3 AI and the Environment
9.4 Management of Natural Disasters
9.4.1 Flooding and Flood Management
9.4.2 Flood Defense
9.4.3 Earthquakes, Windstorms, and Forest Fires
9.5 Conclusion
9.6 Notes
Chapter 10 Employment, Industry, and Agriculture
10.1 Introduction
10.2 Employment
10.2.1 Unemployment
10.3 AI and Industry
10.3.1 State-Owned Enterprises
10.3.2 China Model
10.3.3 South African Model
10.3.4 UK Model
10.3.5 SOEs in the United States
10.4 Agriculture
10.4.1 The Role of AI in Agricultural Policy
10.4.2 The Role of AI in Environmental Issues
10.5 Conclusion
10.6 Notes
Chapter 11 The Role of the State
11.1 Introduction
11.2 What Is the Role of the State?
11.3 What Is Surveillance?
11.4 Reasons for Surveillance
11.5 Surveillance Capitalism
11.6 Surveillance in Covid “Track and Trace”
11.7 Data Justice and Independent Oversight
11.8 A Contrary View
11.9 The Ethics of Surveillance
11.10 Nudging the Citizen
11.11 Conclusion
11.12 Notes
Chapter 12 Risk and Cybercrime
12.1 Introduction
12.2 The Nature of Risk
12.2.1 Management of Risk
12.2.2 Three Lines of Risk Defense
12.3 Roles and Responsibilities in the Public Sector
12.4 Examples of Risk
12.4.1 Technology and System Failure
12.4.2 Data Security and Privacy
12.4.3 Employee Error
12.4.4 Failure of Processes, Systems, and Policies
12.4.5 Reputational Risk
12.4.6 External Risk
12.5 Cybercrime in the Public Sector
12.6 Prevention of Cybercrime and Protection from It
12.6.1 Air Gapping
12.6.2 Supply Chain Vulnerability
12.6.3 Impact on Insurance Coverage
12.7 The Use of AI in Managing Risk
12.8 Conclusion
12.9 Notes
Chapter 13 Implementation – Leadership and Management
13.1 Introduction
13.2 Leadership
13.2.1 Transfer of Private Sector Leaders to the Public Sector
13.3 Leaders or Managers?
13.4 Managing the Mission
13.4.1 Creating the Mission
13.4.2 Prioritization: Where to Start?
13.4.3 Communicating the Mission Statement
13.5 Management of Resources
13.5.1 Technical versus Traditional
13.5.2 Specialist versus Generalist
13.5.3 Training and Education
13.6 Management of Key Stakeholders
13.6.1 Worker Representation and Trade Unions
13.6.2 US Policy Recommendations
13.6.3 German Policy Recommendations
13.6.4 “Dignity at Work” and Working from Home
13.7 Conclusion
13.8 Notes
Chapter 14 Further Implementation Issues
14.1 Introduction
14.2 A Theoretical Approach to Change
14.3 Managing the Problem of Bias
14.3.1 Data Exclusion from Marginalized Communities
14.3.2 Locational Data Issues
14.4 Operational Considerations
14.4.1 Piloting and Test Running the System
14.4.2 Measuring Benefit
14.4.3 Independent Review
14.5 Outsourcing, Partnering, and Supply Chain Management
14.6 The Concept of “Nudge”
14.7 Global Considerations
14.8 Conclusion
14.9 Notes
Chapter 15 Conclusion
15.1 Reflections
15.2 AI and the Real Pace of Change
15.3 Measuring ROI – More Art Than Science?
15.4 AI and Stimulation of Wider Reforms
15.5 The Role of Government in Public Sector Transformation
15.6 Moving the Goalposts
15.7 Notes
Appendix A: The Seven Principles of Public Life
Note
Appendix B: Transformation Roadmap for Public Services
Appendix C: List of Tables
Appendix D: List of Figures
Index
EULA