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 Tim Berners-Lee. This legacy of innovation continues as the Turing Institute gears up for its AI Summit in March, which will undoubtedly build upon discussions from the Bletchley Park conference last November. These gatherings have once again placed Britain at the forefront of AI dialogue, fostering global discussions on governance, new breakthroughs, and visions for smart government technology of the future.
As the benefits of AI become increasingly prevalent, many private sector enterprises are gradually integrating AI into their operations. Energy firms, for instance, are tapping into smart meter usage data for dynamic pricing, while transport companies are employing similar tactics to ensure their seats sell at maximum prices. AI has simplified market analysis, enabling private companies to boost profits efficiently and dynamically, without the extensive effort traditionally associated with price setting.
This raises a key question – why is AI not being utilised similarly in the public sector? In UK infrastructure, AI usage is sporadic, particularly in entities that were once public but are now privatised. While AI holds tremendous potential for enhancing service quality, its deployment is often patchy and driven by profitability. This issue is compounded by the widely recognised critique of privatisation: companies with monopoly status often lack the incentive to improve service quality. We must consider whether such infrastructure companies can be trusted to prioritise delivery of high-quality services and efficiency through AI, or whether it will be clumsily applied with vague aims of skimming extra profit.
If the age-old argument for privatisation has been the promise of more efficient service delivery, then the advent of AI introduces a new suite of tools – allowing public bodies to not only match this efficiency, but also to potentially surpass the private sector. These innovations promise to save central government costs and improve the quality of services, provided the government is ready to embrace them. The days of the term ‘nationalisation’ conjuring images of surplus civil servants arrayed in rows within vast offices, may soon come to pass. The dreaded Quango archetype, ever-expanding in size and cost, without matching such gains in productivity, could soon become a label of the past.
Such new-age public entities have the potential to use modern tech and AI to fully streamline the delivery of public services, whilst keeping costs to the absolute minimum for the taxpayer. This could represent a new direction for the management of British infrastructure. Whilst tech and AI are gradually being hijacked by the private sector, to maximise profits, nationalised entities could employ the same approaches instead to minimise costs, both to governments and to the consumers, in a double-pronged delivery of efficiency.
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 the firing up of power stations, based on localised demand forecasts. Precise data analytics eliminate the need for local management of services, when spatial differences in 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 ground-breaking and high-quality software emerging out of Silicon Valley has been produced on comparatively lower budgets, with fewer resources, and by smaller teams of engineers. This raises the question: where did the UK government go wrong in their approach?
While countries like France and South Korea use state-owned organisations to efficiently execute infrastructure projects, the UK and other Anglophone nations often face criticism for allowing costs to spiral out of control due to reliance on private consulting firms. As we witness the proposals for £300 million to be invested by the government in AI development, it is crucial to scrutinise the funding model of these endeavours. The developers who write software code are the key resource in such tech projects, so it is granted that the government will seek to hire many. However, these arbitrarily high figures given for funding may trigger alarm bells among those who are familiar with the longstanding issues of overspending, and inflated costs in government projects.
Indeed, it seems like our government may be prepared to mis-appropriate 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 laughing stock 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.
In fact, it could be argued that we are in a unique position whereby we could act as an example or testing ground for AI use in government, given our small size as a nation, and sufficient technological infrastructure already in place. Again, if we do not make the leap ourselves to pioneer governmental AI systems, then another country will, and we will have missed our opportunity to provide global influence.
As a semi-regulated economy embracing capitalist principles, 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.
It also must be said, that if we do not act and start developing these frameworks as a public endeavour, there will soon arise a fractured mess of different private players, competing to fill this niché, and likely possessing very little cohesion or compatibility with one another. This would be a disaster for our infrastructure, stalling daily life, technological progress, and potentially stagnating our economic growth, whilst nations with more centralised systems would be able to continue without such hinderance. A clean, minimalist, and efficient AI framework running in the background of our everyday lives would allow us to get on with making more progress as a nation and economy.
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, but not to our benefit. Instead, they too may use AI primarily to reduce their workforce, but without passing on any cost savings to the consumers. The more we delay integrating AI into government operations, the more we risk it being misappropriated for serving big businesses. Certain entities would continue to overcharge us, yet no longer would be able to offset this by providing as many job opportunities as they previously might have.
A firm stance must be taken, where we skip past any initial grief, accepting that yes – AI will reshape the job market, but at least we have the power in our hands to use it for the wider benefit of our nation. That is, to reduce costs to the public, to streamline government services and infrastructure, and to out-compete the private sector in efficiency – if we act now.
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