Discover how data, analytics, and AI will transform public services for the better
In AI and the Future of the Public Sector: The Creation of Public Sector 4.0, renowned executive and consultant Tony Boobier delivers a comprehensive reference of the most relevant and central issues regarding the adoption and implementation of AI in the public sector. In the book, you'll find out why data and analytics are the solution to significant and ongoing problems in the public service relating to its ability to effectively provide services in an environment of reduced funding. You'll also discover the likely impact of future technological developments, like 5G and quantum computing, as well as explore the future of healthcare and the effective digitalization of the healthcare industry.
The book also offers:
- Discussions of policing 4.0 and how data and analytics will transform public safety
- Explorations of the future of education and how ai can dramatically enhance educational standards while reducing costs
- Treatments of the internationalization of public services and its impact on agencies and departments everywhere
A can't-miss resource for public sector employees at the managerial and professional levels, AI and the Future of the Public Sector is an insightful and timely blueprint to the effective use of artificial intelligence that belongs in the bookshelves of policy makers, academics, and public servants around the world.
Table of Contents
Acknowledgments xv
About the Author xvii
Introduction xix
Chapter 1
Understanding the Key Building Blocks of Progress 1
1.1 Introduction 1
1.2 Key Building Blocks of Data Science and AI 2
1.2.1 Data Acquisition 2
1.2.2 Data Maintenance 2
1.2.3 Analysis 3
1.2.4 Communication 3
1.2.5 Machine Learning 4
1.2.6 Artificial Intelligence 4
1.2.7 Advantages and Disadvantages 4
1.2.8 Four Key Focuses for Future AI 5
1.3 Quantum Computing 7
1.3.1 What Is Quantum Computing? 7
1.3.2 Impact on Cybersecurity 9
1.4 Proliferation of Devices 9
1.5 5G and the Impact of Advanced Communications 11
1.5.1 Global Transformation 12
1.6 Public Sectors 4.0 12
1.7 Conclusion 14
1.8 Notes 15
Chapter 2
Office of Finance 17
2.1 Introduction 17
2.2 Forecasting and Public Finance Management 18
2.3 Forecasting 19
2.3.1 Qualitative Forecasting 19
2.3.2 Quantitative Forecasting 20
2.3.3 Forecasting for Public Sector Transformation 21
2.3.4 Managing Risk and Uncertainty 22
2.3.5 Forecasting in IT Projects 23
2.3.6 The Move Toward Activity-Based Costing 24
2.3.7 Hard Benefits and Soft Benefits 24
2.3.8 Enterprise Resource Planning 26
2.3.9 AI and Governmental Administration 28
2.3.10 Global Partnership on AI 29
2.4 Conclusion 30
2.5 Notes 30
Chapter 3
Public Order and Safety 33
3.1 Introduction 33
3.2 The Future of Policing in an AI Era 33
3.2.1 Transformation of Police Work 34
3.2.2 Criminal Use of AI 36
3.2.3 Police Use of New Technologies 36
3.2.4 Case Studies in Policing 37
3.2.5 Policing in China 38
3.2.6 Forward-Looking Policing 39
3.3 AI in Policing 41
3.3.1 Impact on Police Behavior 42
3.4 The Citizen as a Key Component of Future Policing 42
3.5 Police and Location Analytics 43
3.6 Policing Summary 44
3.7 Border Security and AI 45
3.8 Customs Reform 46
3.8.1 The Citizen and Taxation 47
3.9 Fire Safety and AI 48
3.9.1 Natural Fire Prevention 49
3.9.2 Prevention of Urban Fires 49
3.9.3 Smart Homes and Fire Detection 49
3.9.4 Commercial Fire Prevention 50
3.9.5 Firefighting Using AI 50
3.9.6 Fire Station Locations 51
3.10 Conclusion 51
3.11 Notes 52
Chapter 4
Personal Social Services 55
4.1 Introduction 55
4.2 Care Homes 56
4.2.1 The UK Model 57
4.2.2 Care Homes in Japan 59
4.2.3 The Canadian Picture 60
4.2.4 The Emergence of AgeTech 60
4.2.5 Going Forward 61
4.2.6 Conclusion 61
4.3 Impact on Children 62
4.4 Mental Health 64
4.5 Social Protection 66
4.5.1 Social Risk Framework 67
4.6 Employment and Benefit Management 70
4.7 Conclusion 72
4.8 Notes 73
Chapter 5
Health 77
5.1 Introduction 77
5.2 Digitalization and Its Importance in Healthcare 77
5.2.1 Different Categories of Data Sources in Healthcare 78
5.3 Medical Monitoring and Biosensors 79
5.3.1 Use of Biosensors in Mental Health 81
5.4 Innovating to Zero in Healthcare 82
5.4.1 Zero Invasive Surgery 82
5.4.2 Zero Waste Management 83
5.4.3 Zero Surgical Errors 84
5.5 Tissue Engineering 84
5.6 Cybernetics 85
5.7 Advancements in Drug Creation and Treatment 86
5.8 Case Studies in Healthcare 87
5.8.1 Ping An Good Doctor 87
5.8.2 Cancer Screening Case Study 87
5.9 Paramedics and AI 88
5.10 Cybersecurity in Healthcare 89
5.11 Conclusion 90
5.12 Notes 91
Chapter 6
Education 93
6.1 Introduction 93
6.2 Learning for the Future 94
6.3 Teaching in the Future 96
6.3.1 The Use of AI for Predicting Exam Success 97
6.4 AI and Language in the Classroom 98
6.4.1 Automated Essay Scoring 98
6.4.2 Removing Communication Barriers 99
6.5 Robots in the Classroom 99
6.6 The Shortage of Tech Talent 100
6.7 Case Studies in Education 101
6.8 Conclusion 101
6.9 Notes 102
Chapter 7
Defense 105
7.1 Introduction 105
7.2 Use Cases of AI in Defense 106
7.2.1 Intelligence, Surveillance, and Reconnaissance 107
7.2.2 Logistics 108
7.2.3 Cyberspace Operations 108
7.2.4 Information Operations and “Deep Fakes” 108
7.2.5 Command and Control 108
7.2.6 AI and Augmented Reality Soldiers 109
7.2.7 Semi-Autonomous and Autonomous Vehicles 109
7.3 Ethical Issues 110
7.4 Drones 111
7.5 Conclusion 113
7.6 Notes 114
Chapter 8
Smarter Cities and Transportation 115
8.1 Introduction 115
8.2 Smarter Cities 115
8.2.1 Smart Infrastructure 116
8.2.2 Smart Transportation 116
8.2.3 Street Lighting 116
8.2.4 Water Utilities 117
8.2.5 Emergency Services 117
8.2.6 Waste Collection and Disposal 118
8.2.7 Maintenance of Public Places 118
8.2.8 Humans as Devices 118
8.2.9 Data Challenges for Smart Cities 119
8.3 Transportation 119
8.3.1 Traffic Management 120
8.3.2 Road Safety 120
8.3.3 Highway Maintenance 121
8.3.4 Autonomous Trams 121
8.3.5 Autonomous Taxis 123
8.4 Railways and the Future of Rail 123
8.4.1 Net Zero in Rail 124
8.4.2 AI and Effective Rail Timetabling 125
8.5 Air Travel 126
8.6 Conclusion 128
8.7 Notes 128
Chapter 9
Housing and the Environment 131
9.1 Introduction 131
9.2 AI in Social Housing 131
9.2.1 Risk Management in Social Housing 133
9.2.2 Transforming the Tenant Experience 133
9.2.3 Case Study - Housemark Pilot 134
9.2.4 Social Housing Fraud 135
9.2.5 Tenant Viewpoint 136
9.2.6 AI as a Virtual Housing Assistant 137
9.2.7 Chatbots in Social Housing 137
9.3 AI and the Environment 138
9.4 Management of Natural Disasters 139
9.4.1 Flooding and Flood Management 139
9.4.2 Flood Defense 140
9.4.3 Earthquakes, Windstorms, and Forest Fires 141
9.5 Conclusion 141
9.6 Notes 142
Chapter 10
Employment, Industry, and Agriculture 145
10.1 Introduction 145
10.2 Employment 145
10.2.1 Unemployment 146
10.3 AI and Industry 148
10.3.1 State-Owned Enterprises 149
10.3.2 China Model 150
10.3.3 South African Model 150
10.3.4 UK Model 150
10.3.5 SOEs in the United States 151
10.4 Agriculture 151
10.4.1 The Role of AI in Agricultural Policy 152
10.4.2 The Role of AI in Environmental Issues 153
10.5 Conclusion 153
10.6 Notes 154
Chapter 11
The Role of the State 157
11.1 Introduction 157
11.2 What Is the Role of the State? 157
11.3 What Is Surveillance? 159
11.4 Reasons for Surveillance 160
11.5 Surveillance Capitalism 161
11.6 Surveillance in Covid “Track and Trace” 163
11.7 Data Justice and Independent Oversight 164
11.8 A Contrary View 166
11.9 The Ethics of Surveillance 167
11.10 Nudging the Citizen 168
11.11 Conclusion 170
11.12 Notes 171
Chapter 12
Risk and Cybercrime 173
12.1 Introduction 173
12.2 The Nature of Risk 173
12.2.1 Management of Risk 174
12.2.2 Three Lines of Risk Defense 176
12.3 Roles and Responsibilities in the Public Sector 176
12.4 Examples of Risk 176
12.4.1 Technology and System Failure 177
12.4.2 Data Security and Privacy 178
12.4.3 Employee Error 179
12.4.4 Failure of Processes, Systems, and Policies 180
12.4.5 Reputational Risk 181
12.4.6 External Risk 183
12.5 Cybercrime in the Public Sector 183
12.6 Prevention of Cybercrime and Protection from It 186
12.6.1 Air Gapping 186
12.6.2 Supply Chain Vulnerability 186
12.6.3 Impact on Insurance Coverage 187
12.7 The Use of AI in Managing Risk 187
12.8 Conclusion 188
12.9 Notes 189
Chapter 13
Implementation - Leadership and Management 191
13.1 Introduction 191
13.2 Leadership 192
13.2.1 Transfer of Private Sector Leaders to the Public Sector 195
13.3 Leaders or Managers? 196
13.4 Managing the Mission 197
13.4.1 Creating the Mission 197
13.4.2 Prioritization: Where to Start? 198
13.4.3 Communicating the Mission Statement 199
13.5 Management of Resources 201
13.5.1 Technical versus Traditional 201
13.5.2 Specialist versus Generalist 201
13.5.3 Training and Education 202
13.6 Management of Key Stakeholders 204
13.6.1 Worker Representation and Trade Unions 205
13.6.2 US Policy Recommendations 207
13.6.3 German Policy Recommendations 208
13.6.4 “Dignity at Work” and Working from Home 209
13.7 Conclusion 211
13.8 Notes 211
Chapter 14
Further Implementation Issues 213
14.1 Introduction 213
14.2 A Theoretical Approach to Change 213
14.3 Managing the Problem of Bias 217
14.3.1 Data Exclusion from Marginalized Communities 219
14.3.2 Locational Data Issues 220
14.4 Operational Considerations 220
14.4.1 Piloting and Test Running the System 220
14.4.2 Measuring Benefit 221
14.4.3 Independent Review 222
14.5 Outsourcing, Partnering, and Supply Chain Management 222
14.6 The Concept of “Nudge” 226
14.7 Global Considerations 228
14.8 Conclusion 231
14.9 Notes 232
Chapter 15
Conclusion 233
15.1 Reflections 233
15.2 AI and the Real Pace of Change 234
15.3 Measuring ROI - More Art Than Science? 235
15.4 AI and Stimulation of Wider Reforms 236
15.5 The Role of Government in Public Sector Transformation 237
15.6 Moving the Goalposts 238
15.7 Notes 239
Appendix A: The Seven Principles of Public Life 241
Appendix B: Transformation Roadmap for Public Services 243
Appendix C: List of Tables 245
Appendix D: List of Figures 247
Index 249
