Historically, Britain has set benchmarks that have been embraced worldwide, such as standardising the railway gauge, establishing Greenwich Mean Time, and pioneering web standards through the work of Tim Berners-Lee. This legacy of innovation continues as the Turing Institute gears up for its AI Summit in March, furthering discussions from the Bletchley Park conference last November. These gatherings once again place Britain at the forefront of innovation, fostering global discussion on governance, new breakthroughs, and visions for government technology of the future.
As the benefits of AI become increasingly prevalent, many private sector enterprises are gradually integrating AI into their operations. For instance, energy companies are using smart meter data for predictive demand forecasting, meanwhile transport companies are employing dynamic pricing to sell seats at maximum prices. AI has simplified market analysis, enabling the identification of profit opportunities efficiently and rapidly, without traditional market analysis.
This raises a key question: Why is AI not being used similarly in the public sector? In UK infrastructure, whilst AI has tremendous potential to improve service quality, its deployment is often patchy. This issue is compounded by a widespread lack of incentive amongst monopolies to improve service quality without increased revenue opportunities. We must consider whether such infrastructure companies will prioritise delivery of high-quality services and efficiency through AI, or whether it will be clumsily applied, with extra costs passed on to the consumer.
If the age-old argument for privatisation has been more efficient service delivery, then AI advancements offer a brand-new suite of tools that could enable public sector organisations to not only match this efficiency but also to potentially surpass the private sector. Such innovations have the potential to reduce central government burden and improve the quality of services, provided they are readily embraced.
The term ‘nationalisation’, conjuring images of civil servants excessively sprawled across vast offices, may soon come to pass. The dreaded archetypal quango, ever-expanding in size and cost whilst diminishing in productivity, could soon become a stereotype of the past.
Such new-age public sector entities have the potential to use modern tech and AI to fully streamline the delivery of public services, whilst keeping public costs to the absolute minimum.
To provide an example, we can look at the energy sector. With many homes now equipped with smart meters, we have access to both live and historical data, enabling us to make informed predictions about energy usage patterns. This live data could be used to strategically schedule generation at power stations, based on localised demand forecasts. Precise data analytics eliminate the need for local management of services when spatial trends can be monitored at a national level.
Unfortunately, the UK government has a legacy of poor project management and overspending in tech projects, a widely publicised example of this being the development of the Test and Trace app. This £23 billion endeavour made headlines for its security flaws and antiquated structure, notably for the storing of patient data in the XLS Excel spreadsheet file format from the 90s.
It is still difficult to fathom how the development of such a primitive app accumulated such high costs. In comparison, much of the groundbreaking and high-quality software emerging out of Silicon Valley start-ups is produced on comparatively lower budgets, with fewer resources and by smaller teams of engineers. So, where did the UK government go wrong in its approach?
The UK and other Anglophone nations often face criticism for allowing costs to spiral out of control due to reliance on private consulting firms (when compared to similar economies in Europe and East Asia). Indeed, it seems like our government may be prepared to misappropriate tech once again, as a cover for disorganised public spending, instead of pursuing with integrity what technology has long been intended for – to increase efficiency, to reduce the burden of costs and labour upon a society, and to unlock better ways of living for people.
We can forget our global tech aspirations if the same charades and old tricks that were pulled during the Test-and-Trace or High-Speed 2 disasters are to be pulled again. Such outcomes would certainly serve to make us a laughingstock of the world, rather than build our reputation. The UK needs to seize every opportunity to be taken seriously as a global competitor in AI and in its public applications.
As a semi-regulated economy that still embraces enterprise and innovation, we represent a mid-point between the ultra-free market landscape of the United States and the largely state-controlled economy of China. Thus, our approach to governmental AI could turn out to be compatible with a multitude of nations and their systems, making it potentially suitable for wide adoption. Furthermore, our small size as a nation and sufficient technological infrastructure already in place make us a good testing ground for AI use in government.
If we do not seize the opportunity ourselves to pioneer governmental AI systems, then another country will, and we will have missed an opportunity to provide global influence.
It’s also likely that if the public sector does not pioneer such systems, there may instead arise a fractured mess of different systems from the private sector, which will by design not be compatible with one another. Thus, we shall have to wait for them to compete each other out of the market before we can get on with reaping the benefits of such systems.
This would be a setback for our infrastructure, stalling daily life and technological progress, and lead to unmet potential, whilst nations embracing standardised/centralised systems would be able to outpace us. A standardised and efficient set of technology systems ‘running in the background of our everyday lives’ would allow us to get on with making more progress in the other areas of our economy and daily lives.
A difficult truth that we may have to acknowledge is that we are now at the brink of a great shift in the structure of the service industry. Advancements in AI are already affecting workforces, which are seeing certain roles gradually scaled down, whilst other opportunities are created.
However, we are at a point where we must boldly embrace our future, regardless of difficulties, seeking to seize AI as a national endeavour. If the public sector fails to adopt AI for cost reduction to the consumer, then the private sector will undoubtedly capitalise on it. The job losses will still come, but consumers will have even less to make up for it.
A firm stance must be taken. We have the power in our hands to use public sector tech and AI for the wider benefit of our nation. That is, to reduce costs to the public, to streamline government services and infrastructure, and to outcompete overseas private enterprises in efficiency – if we act now.
Leave a Reply