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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Serie: Wiley Finance Editions
- Sprache: Englisch
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.
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Veröffentlichungsjahr: 2022
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Table of Contents
Cover
Title Page
Copyright
Dedication
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
1.3 QUANTUM COMPUTING
1.4 PROLIFERATION OF DEVICES
1.5 5G AND THE IMPACT OF ADVANCED COMMUNICATIONS
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
2.4 CONCLUSION
2.5 NOTES
CHAPTER 3: Public Order and Safety
3.1 INTRODUCTION
3.2 THE FUTURE OF POLICING IN AN AI ERA
3.3 AI IN POLICING
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
3.9 FIRE SAFETY AND AI
3.10 CONCLUSION
3.11 NOTES
CHAPTER 4: Personal Social Services
4.1 INTRODUCTION
4.2 CARE HOMES
4.3 IMPACT ON CHILDREN
4.4 MENTAL HEALTH
4.5 SOCIAL PROTECTION
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
5.3 MEDICAL MONITORING AND BIOSENSORS
5.4 INNOVATING TO ZERO IN HEALTHCARE
5.5 TISSUE ENGINEERING
5.6 CYBERNETICS
5.7 ADVANCEMENTS IN DRUG CREATION AND TREATMENT
5.8 CASE STUDIES IN HEALTHCARE
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
6.4 AI AND LANGUAGE IN THE CLASSROOM
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
7.3 ETHICAL ISSUES
7.4 DRONES
7.5 CONCLUSION
7.6 NOTES
CHAPTER 8: Smarter Cities and Transportation
8.1 INTRODUCTION
8.2 SMARTER CITIES
8.3 TRANSPORTATION
8.4 RAILWAYS AND THE FUTURE OF RAIL
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
9.3 AI AND THE ENVIRONMENT
9.4 MANAGEMENT OF NATURAL DISASTERS
9.5 CONCLUSION
9.6 NOTES
CHAPTER 10: Employment, Industry, and Agriculture
10.1 INTRODUCTION
10.2 EMPLOYMENT
10.3 AI AND INDUSTRY
10.4 AGRICULTURE
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
12.3 ROLES AND RESPONSIBILITIES IN THE PUBLIC SECTOR
12.4 EXAMPLES OF RISK
12.5 CYBERCRIME IN THE PUBLIC SECTOR
12.6 PREVENTION OF CYBERCRIME AND PROTECTION FROM IT
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
13.3 LEADERS OR MANAGERS?
13.4 MANAGING THE MISSION
13.5 MANAGEMENT OF RESOURCES
13.6 MANAGEMENT OF KEY STAKEHOLDERS
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
14.4 OPERATIONAL CONSIDERATIONS
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
End User License Agreement
List of Tables
Introduction
TABLE I.1 Possible Risk Implications of AI in Public Services
Chapter 1
TABLE 1.1 Advantages of AI
TABLE 1.2 Disadvantages of AI
TABLE 1.3 Number of Connected Devices
TABLE 1.4 Growth in Volume of Digitally Stored Information
TABLE 1.5 Issues That Emerge from Data Proliferation
Chapter 2
TABLE 2.1 Share of Transformation Effort That Includes Objectives
TABLE 2.2 Top Consumers of ERP Software
Chapter 3
TABLE 3.1 Police Technology Focus
Chapter 4
TABLE 4.1 Social Protection Strategies
TABLE 4.2 Social Risk Framework Tool
TABLE 4.3 Main Sources of Risk
TABLE 4.4 Use of Technology in Social Care Programs
Chapter 6
TABLE 6.1 Job Growth by 2030
Chapter 8
TABLE 8.1 Future Competencies for Pilots
Chapter 9
TABLE 9.1 Virtual Housing Assistant Capabilities
Chapter 10
TABLE 10.1 Different Approaches to Unemployment
Chapter 12
TABLE 12.1 Types of Risk
TABLE 12.2 Three-Stage Approach to Risk Management
TABLE 12.3 Risk Roles and Responsibilities in the Public Sector
Chapter 13
TABLE 13.1 Differences in Public and Private Sector Leadership Characteristi...
TABLE 13.2 Five Shifts in Public Sector Leadership Thinking
TABLE 13.3 Creating the Public Services Mission
TABLE 13.4 Marketing Strategies for Public Sector Transformation
TABLE 13.5 Key Elements of Value in Workplace Dignity
Chapter 14
TABLE 14.1 Pillars of Change and Comparison of Political and Public Sector I...
TABLE 14.2 Organizational Pathways to Change
TABLE 14.3 Seven-Point Framework for Removal of Ethical Bias
TABLE 14.4 Nudge and MINDSPACE
TABLE 14.5 Three-Step Approach to Behavioral Science
TABLE 14.6 Factors Affecting the Nation State
List of Illustrations
Introduction
FIGURE I.1 Phases of Change of Maturity of AI in the Public Sector
Chapter 1
FIGURE 1.1 Pyramid of Analytical Maturity
FIGURE 1.2 Singularity and Immortality
Chapter 4
FIGURE 4.1 Chilean Social Register
Chapter 5
FIGURE 5.1 Examples of Healthcare Data
FIGURE 5.2 Ping An Good Doctor
Chapter 6
FIGURE 6.1 New Models of Teaching
Chapter 7
FIGURE 7.1 Typical Digital Defense Implementation Framework
Chapter 10
FIGURE 10.1 Susceptibility of Job Losses to AI.
Chapter 13
FIGURE 13.1 Evolution of Capabilities
FIGURE 13.2 Stakeholder Relations Influence Framework
Chapter 14
FIGURE 14.1 Alternative Subcontracting Models
Guide
Cover
Table of Contents
Title Page
Copyright
Dedication
Acknowledgments
About the Author
Introduction
Begin Reading
Appendix A: The Seven Principles of Public Life
Appendix B: Transformation Roadmap for Public Services
Appendix C: List of Tables
Appendix D: List of Figures
Index
End User License Agreement
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AI and the Future of the Public Sector
The Creation of Public Sector 4.0
TONY BOOBIER
This edition first published 2022
Copyright © 2022 by John Wiley & Sons, Ltd.
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Library of Congress Cataloging-in-Publication Data is Available:
ISBN 9781119868101 (Hardback)ISBN 9781119868118 (ePDF)ISBN 9781119868125 (ePub)
Cover Design: WileyCover Image: © oxygen/Getty Images
This book is dedicated to all the public sector workers who not only performed miracles but kept society running during the pandemic.
Acknowledgments
The acknowledgment section is principally about saying thank you. My first point of call is to thank Gemma Valler at Wiley, who has constantly believed in me and allowed me to write about this most important of subject areas. Thank you also to the remainder of the Wiley team.
Closer to home, I must of course acknowledge my wife Michelle and the rest of the family who have supported me.
George Orwell once said that he wrote for four reasons:
Sheer egotism, which for him was the joy of being talked about and remembered.
Aesthetic enthusiasm, which was about choosing and arranging the words and chapters in the right order.
Historical impulse, which is about storing information up for posterity.
Political purpose, with “politics” being used in the widest possible sense, which is about pushing the world in a particular direction.
Focusing especially on the final point, this book was written not only in recognition of the very great importance of the public sector in current times but also to recognize the challenges of that sector going forward. These are pressures of cost, political will, and the continued need of the citizen for public services, as well as the impact of technology.
Throughout the text, I have relied on many different opinions, as evidenced by the number of references contained within this book. I would also like to thank those contributors for their insight and inspiration. Where specific products and services are mentioned within the text, this is by way of example and although doubtless they are fine organizations, there are no commercial relationships between them and the author, and no recommendation should be inferred from their inclusion.
About the Author
Tony Boobier is an independent advisor with over 40 years of broad-based international experience who supports startups, established organizations, and individual executives. Qualified in engineering, marketing, insurance, and supply chain management, and having held several fellowships, he has a deep understanding of the practical applications of advanced analytics and AI for improving the management and delivery of products and services.
A frequent public speaker and commentator on industry matters, especially the use of AI, he is a strong advocate for the use of business-led, enterprise-wide analytics and AI to enhance service and reduce cost. He is the author of Analytics for Insurance: The Real Business of Big Data (2016); Advanced Analytics and AI: Impact, Implementation, and the Future of Work (2018); and AI and the Future of Banking (2020), all published by Wiley. He lives near London, UK.
Introduction
There is a price to be paid for everything. The enormous payments made by individual governments around the world to support economies as a result of the COVID-19 pandemic will need somehow to be funded. The additional impact of other subsequent world events also cannot be discounted.
Cutting the costs of the public sector budget is inevitably in the cards, sooner or later. Even so, previous experience has shown that an approach of austerity to control costs isn't always best. Austerity as a solution has historically been seen as a major contributor to political tension, as evidenced by governmental approaches following the global financial crisis of 2007–2008. Some suggest that austerity could be the best and perhaps only way forward, especially when we are in a low-interest-rate environment; low interest rates are usually only a temporary relief, and higher interest rates do not normally provide a panacea.
The mood to managing debt has changed from a decade ago. Then, Germany's Chancellor Angela Merkel pressured the European states to reduce their debt levels to preserve the integrity of the Euro. Nowadays, economists such as Ulrik Knudsen, appointed Deputy Secretary General of the Organisation for Economic Co-operation and Development (OECD) in 2019, are calling austerity “an old-fashioned way of thinking” and one that leads ultimately to isolationism.
Although perhaps in a less dramatic form, it is almost certain that there will be a financial impact on the public purse as a result of the pandemic. Savings will have to be made. For many sectors of society, and despite political reassurances, essential reductions will be made in public funding. While the proverbial barrel is not yet dry, the amounts available from governments to prop up public services are likely to diminish. This scarcity will affect services as diverse as policing, social services, medical care, and public administration. It will also affect both national and regional strategies. At an individual level, it will affect the funding of leisure services for the public, as well as how we are policed. It will also have an impact on matters as mundane as how often the streets are cleaned.
All of these effects, and others, will force us to find ways of providing services at lower cost. Budgetary costs will inevitably translate into manpower reduction and possibly higher levels of unemployment. For many sectors, there is likely to be a struggle to maintain the level of current services, and the potential is for the frequency and quality of public services to start to fall below our expected standards.
We should not underestimate the size of the public sector. In the majority of countries, public sector expenditure represents 35 to 60% of their GDP. At a global level, between 14% and 19% of all employees are paid from the public purse. Indirectly they are funded by the taxpayer. While one simple argument is to increase the taxpayers' contribution, invariably there are political pressures that relate to that option as a remedy, not least that few political parties have been successful at reelection on a ticket that promises to increase taxation.
The aspect of politics equally cannot be overlooked – although this is not meant to be a book that is political in nature. Rather, governments need to prioritize public services so that funding can be appropriately allocated. This in itself is no small task. How might a government prioritize policing over healthcare, or street cleaning over the care of the elderly? The reality is that all these sectors will need to be maintained in one way or another.
Having created a dark picture for the future, I've written this book as an antithesis to that situation. It aims to provide insight and a way forward, whereby the quality and efficiency of almost all types of public services can be improved through the effective use of data, advanced analytics, and artificial intelligence. It helps provide a road map for an analytically infused future in public services, where improvements can occur (or, at the very least, the quality of services can be maintained) at no additional cost (or maybe even at a reduced cost) to the taxpayer.
Recent developments in analytics and AI are timely. They coincide with our time of greatest need. The advent of ubiquitous devices providing multiple data points, together with new forms of analysis, helps create new insights that will inevitably affect the way in which public services are undertaken. The advent of 5G and ultimately quantum computing will also improve the quantity and quality of data collection and its analysis. However, we need to recognize that this will not be a world taken over by data scientists and computer systems, but rather that there is a need for experienced and trusted practitioners (who might be called “traditionalists”) to ensure that there remains a balance between essential services and effective technology.
Effective implementation requires experts in their fields to be able to interpret the output from data, and from this to create new business models and working practices. This is not simply a matter of digitalizing the present, but also one of reimagining the future.
This book has been written principally for three groups.
First, it is for those directly employed in the public sector who will be faced with the challenge of maintaining and in some cases even improving public services, yet are concerned about or maybe even have a fear about the technologies likely to be used. Those people in this group are key stakeholders, as it will be their knowledge and experience that will play an essential part in the transformation. The range of those involved will extend from those at an operational level to those who act at an executive level. Both of these groups, and all those in between, will benefit from having a single reference point into a complex area.
Second, the book is for those data scientists and AI experts who, while having a knowledge of the “pure” elements of data management and AI will nevertheless have limited appreciation of the key business drivers of various public sector activities, and without whom it will be more difficult to understand how technologies might be best implemented. The nature of the advanced analytics and AI boom will necessarily require a great increase in those who have requisite technology skills. This second group may comprise mature candidates who have decided to retrain to keep up with the times, and also comprise new entrants who have chosen technology as their preferred career.
The third group is a critical component to the process of transformation. These people are those who sit in the Office of Finance and whose job it will be to identify likely returns of investment and also to measure the benefits that accrue. Although effective implementation of AI will bring a combination of hard and soft benefits, it is this group that is most likely to want to measure the financial benefit of AI transformation, especially as the greatest pressure will be on financial control and constraints. For many organizations, the topic of risk management also sits within the Office of Finance, usually assisted by additional forms of governance.
Despite there being many different elements within the public sector, which might be described as “vertical components,” there are also key generic features that apply across almost all of them. Better understanding of these generic features or “horizontal components” leads to greater improvement in knowledge transfer and facilitates a move away from what is seen by many to be a siloed mentality, toward what will be a more holistic approach to the provision of public services.
The scope and breadth of public services is so wide as to render it virtually impossible to cover each and every service in complete detail. Therefore the book will consider some of the key public services, which are dealt with as individual chapters, such as healthcare and defense, but otherwise bundles together other services. This bundling is not arbitrary but rather follows the grouping of public services in the UK Government, which, while not perfect, suffices to provide a framework for the text.
Throughout the book, progress to date in different public sectors will be evidenced where possible by documented case studies that are already in the public domain.
Beyond all this, there are also geographical and demographical issues to consider. The topic of public services has international scope, which is overlaid by cultural aspects and differing types of governmental attitudes. This potentially leads to different nuances in terms of implementation and adoption. Invariably there will also be a different response to some of these ideas dependent on the demography and attitude of the citizen themselves.
The book adopts three key precepts: First and foremost, that it is the citizen who needs to be the overriding concern in these transformations. All that will happen going forward must necessarily be in the interest of the citizen who has to engage with the process, either directly or indirectly. This level of engagement might demand that the citizen needs to undergo some shifts in thinking, and to have a change of mindset. One of these changes will necessarily relate to the topic of data capture, its security, and how this data is used. Some citizens, perhaps even a sizeable proportion, will be concerned about this development. The book will necessarily reflect on the role of the State, dealing with some of the implications that attach to that consideration, and how this particular challenge might be addressed going forward.
Public opinion is mixed on the use of AI in the public sector. A 2019 YouGov survey reported that nearly half of people (45%) don't like the idea of humans not being involved in decisions that affect them:
49% thought that the public sector should understand AI more before they start to use it.
24% think it will lead to job losses.
23% think that there won't be any benefits for local authorities if they use AI.
25% worry about public accountability.
23% worry about decisions being made logically rather than ethically.
1
In social services, according to feedback from the survey, practitioners believe, for example, that they “need to see the whites of their clients' eyes” rather than rely on algorithms.
The second precept is that it is possible to maintain and almost certainly improve service at the same time costs are being reduced. This may seem to be a paradox to many, yet the reality is that public services are not only often frictional in operation, but also comprise unnecessary management layers that technology will reduce. In other words, public services of the future will comprise a flatter, data-driven, and overall more efficient “friction-free” service. According to former UK Government chief operating officer Stephen Kelly, “The best way to protect the future of local council services and communities is through the smart use of technology.”2
The third precept is that some of the changes discussed here may require an abandonment of traditional ideas. In a 2021 newspaper article, author Daniel Kahneman reinforced that point, and commented on the potential difficulties, saying, “When linear people are faced with exponential change, they're not going to be able to adapt to that very easily. So clearly, something is coming…. And clearly AI is going to win [against human intelligence]. It's not even close. How people are going to adjust to this is a fascinating problem – but one for my children and grandchildren, not me.”3
The likelihood is that this isn't a matter that will wait for those future generations but rather that the need is more pressing in terms of the timescale involved. It will not only affect Kahneman's children and grandchildren, but almost certainly will affect him (and you) as well.
In a future for public services that has some degree of uncertainty, there are inevitable risks. It's a topic that will reemerge throughout this book. These risks were captured in the 2019 report for Zurich Municipal, entitled “Artificial Intelligence in the Public Sector,” and are reinterpreted in Table I.1.
Many of these elements are relatively straightforward, but one of these, the Paradox of Automation, requires a little more explanation. The term originates from the book Messy by Tim Harford, based on the crash of Air France Flight 447 in June 2009. In it, Harford writes “… the more efficient the automated system, the more crucial the human contribution of the operators…. If an automated system has an error, it will multiply that error until it's fixed or shut down. This is where human operators come in. Efficient automation makes humans more important, not less”4,5
The Paradox of Automation considers the idea that it is unreasonable for humans to leave matters to automated systems for most of the time, and then pay attention only when there is an emergency or when things go wrong. It suggests that if and when human intervention is needed in a world that is more automated, then humans will find it difficult to take appropriate corrective action because of their absence of experience. The development of autonomous vehicles is referenced, for example, as a potential area of concern, as humans might only be needed when an emergency happens, but the principle also extends to the public sector, where matters of life and death could be involved.
TABLE I.1 Possible Risk Implications of AI in Public Services
Physical risks will continue to exist
Can appropriate skills and capabilities be developed quickly enough?
Accountability – who is at fault for failure in complex AI ecosystems?
Do policy makers really understand the technology and its impact?
“Dumb” vs. “Intelligent” AI/“Soft” vs. “Hard” AI
How will change affect employee well-being, their rights, and the nature of employment?
What is the best regulatory framework and how will the Government implement it?
Does the technology need to be owned, or is access to the technology enough?
How to cope with the “Paradox of Automation”
Are black box technologies appropriate in areas of sensitivity?
How can we ensure that algorithms and data are used ethically?
What might be the impact on equality/human rights?
Can humans adequately supervise technology, including self-learning systems?
What is the impact of cyber risk and cyber fraud?
What new commercial risks might arise, and how can these be managed through better contract management?
Traditional vs. “Born Digital” services, that is, new services based on technology
What is the impact on interruption to business?
How will governance be managed? For example will it be “Open” vs. “Closed”?
What democratic oversight will be needed?
What new risk management skill sets are necessary?
The topic of implementation is also a key issue, especially as the public sector has its own considerations when compared to the private sector. This is dealt with in detail, including issues likely to arise and mitigating actions that may be appropriate. The speed of change also needs to be considered, especially within the context of implementation. Key drivers of the rate of change include the:
Degree of pressure on the public purse
Impact of pressure groups, especially, for example, in matters of scrutiny, data privacy, and security
Response of organizations representing public sector employees
Attitude of citizens to perceived improvements or deterioration in public services
Degree to which governments need to put in place safeguards and adequate regulation
Support or otherwise by the media and other social influencers
Rate at which public services organizations accept and endorse advanced technologies into their strategy
FIGURE I.1 Phases of Change of Maturity of AI in the Public Sector
Source: Adapted from “Artificial Intelligence in the Public Sector,” IBM, 2021, https://www.businessofgovernment.org/sites/default/files/Artificial%20Intelligence%20in%20the%20Public%20Sector_0.pdf.
Figure I.1 reflects the phases the public sector may need to pass through when related to the degree of uncertainty of the possible outcome. It suggests a timeline that extends from the near future, say to 2025, and extends that period to as far out as 2050. By that later date, our understanding of the nature of public services themselves is likely to have changed. The question is whether we will recognize public services as being similar to those we experience today or if that change will be dramatic and unrecognizable. After all, 2050 is a mere few decades ahead of us, and is only slightly further in the future when compared to how far the new millennium is behind us.
THE POLITICAL PERSPECTIVE
In considering the use of AI in public services, there is invariably a political aspect that needs to be considered as well. The impact of the pandemic has resulted in many governments making huge payouts and taking on massive debts. The premise of this book is that they might be able and willing to carry on doing so for the moment, and may even continue in the short term to put their hands deeper into their proverbial pockets and provide more money. But there will be a point at which the ultimate bill will need to be paid. Financial engineering by governments may be useful in the relatively short term but cannot go on indefinitely. Some of this burden of repayment will fall on the taxpayer, either at a personal or business level, or will be reflected in savings through reductions in services, or perhaps both.
Neither of these is likely to be particularly attractive at the ballot box. The challenge for governments is not only how to settle the debts but how to implement the essential savings needed in the public sector while at the same time maintaining both public services and public confidence.
In his May 2021 New Statesman essay, former UK Prime Minister Tony Blair reflected on the many particular challenges that faced his own party. He referred to the need for political change against the “backdrop of a real-world transformation,” which he describes as the “central political challenge of our time.” Specifically considering public services, Blair says:
The way we teach and provide medical care and education will change dramatically, and therefore old ways of working will decline. New forms of social ownership will be needed to tackle the housing crisis. Solutions will often be practical, some more associated with traditional left thinking but some more with modern centre-right thinking. It will require steadfast adherence to values but complete agnosticism as to the means of implementing them.6
Beyond this, Blair also considered the impact of technology on infrastructure, transportation, crime, and defense, and reminds the reader that “nations which are first-movers will get a disproportionate advantage.” Blair is not the only political leader who has his eye on AI. In 2018, following an announcement that the French Government was to invest US$1.85 billion over a five-year program, French President Macron commented that “AI will raise a lot of issues in ethics, in politics, it will question our democracy and our collective preferences…. This leads me [sic] to the conclusion that this huge technological revolution is in fact a political revolution.”7
In Germany, former Chancellor Angela Merkel compared the country's reputation for building prestige cars with their own country's developments in AI, saying, “the same brand ‘Made in Germany’ claim must also be a trademark in artificial intelligence,” adding also that “people must be at the center of Germany's understanding of digitalization.” There, as in many other countries, is skepticism about a digital future, especially misuse of personal data as well as fears regarding job losses. German Labor Minister Hubertus Heil aimed to reassure the electorate, saying in 2018, “Concerns over job losses … are very much real. By 2025, some 1.3 million jobs will have been replaced with artificial intelligence but … another 2.1 million jobs will have been created.”8
The picture seems to be the same everywhere you look. Countries politically recognize the importance both of AI and in establishing some form of digital leadership. For many, this is mainly in order to challenge both the United States and China. However, these countries also recognize complex issues of data security, privacy, and intention. Adopting and implementing an AI strategy, while important at a national level, is unlikely in itself to be a vote winner, especially where job losses might be involved.
In conclusion, this book seeks to recognize the impact of data, analytics, and advanced systems in current and future public services. Beyond this, it aims to reflect the differences in nature between varying types of public service, as well as the variation of usage across different geographies. It argues for data-driven transformation as a panacea for the financial pressures brought on by the recent pandemic, but suggests that in any case there is a degree of inevitability that public services will become data and AI driven, and that many if not all of these changes would happen regardless.
In the next chapter, it is recognized that there is likely to be a varying degree of knowledge and understanding of readers of technology matters, so a level-set is initially provided for those with a more basic understanding. Those with greater technical knowledge may choose to pass over this section. It also is an appropriate time to provide some basic insights into the more modern areas of 5G and quantum computing. The concept of “Public Sector 4.0” is also introduced.
NOTES
1
. Dsouza, R. (2021). “Global: More People Worried Than Not About Artificial Intelligence,” YouGov, November 18.
today.yougov.com/content/39497-global-more-people-worried-not-about-artificial-in
.
2
. Zurich Marketing. (2019). “Artificial Intelligence in the Public Sector.” Zurich, September 26.
https://www.zurich.co.uk/news-and-insight/artificial-intelligence-in-the-public-sector-the-future-is-here
.
3
. Adams, T. (2021). “Daniel Kahneman: ‘Clearly AI Is Going to Win. How People Are Going to Adjust Is a Fascinating Problem.’”
The Guardian
, May 16.
https://www.theguardian.com/books/2021/may/16/daniel-kahneman-clearly-ai-is-going-to-win-how-people-are-going-to-adjust-is-a-fascinating-problem-thinking-fast-and-slow
.
4
. Rubenstein, M. (2019). “Air France Flight 447: Ten Years On.”
Degrees of Certainty
(blog), May 8.
https://degreesofcertainty.blog/2019/05/08/air-france-flight-447-ten-years-on/
.
5
. Harford, T. (2016).
Messy: The Power of Disorder to Transform Our Lives
. Riverhead Books.
6
. Blair, T. (2021). “Tony Blair: Without Total Change Labour Will Die.”
New Statesman
, May 11.
https://www.newstatesman.com/labour-in-crisis/2021/05/tony-blair-without-total-change-labour-will-die
.
7
. Thompson, N. (2018). “Emmanuel Macron Talks to WIRED about France's AI Strategy.”
WIRED
, March 31.
https://www.wired.com/story/emmanuel-macron-talks-to-wired-about-frances-ai-strategy
.
8
. Brady, K. (2018). “Germany Launches Digital Strategy to Become Artificial Intelligence Leader.” DW, November 15.
https://www.dw.com/en/germany-launches-digital-strategy-to-become-artificial-intelligence-leader/a-46298494
.
