The spectre of last week’s bond market sell-off hangs over the government’s artificial intelligence strategy. Investors, and voters, want to know where the growth is in the UK economy.
Keir Starmer and the chancellor, Rachel Reeves, believes AI is a significant part of the answer.
The UK has considerable strengths in AI, which can be loosely defined as computer systems performing tasks that typically require human intelligence (ranging from summarising a document to assessing a medical patient’s symptoms and writing emails).
Those strengths include the high-quality research and engineering talent coming out of UK universities and the fact that the country already hosts a number of leading AI companies, led by the UK-founded Google DeepMind.
There are negatives, of which the government is well aware (hence the strategy): building data centres – the central nervous system of AI systems – is a laboriously difficult process in the UK; access to, and the cost of, the vast amounts of energy needed for data centres is also a problem; AI talent and companies can move elsewhere if they get frustrated; and getting regulation right, from safety to copyright, is a difficult balance to strike.
“AI is not a panacea. It’s not magic,” says Theo Bertram, the director of the Social Market Foundation thinktank. “But if you are going to place your bets on a chance for economic growth, then this would be the best place to put it.”
Why is the government investing so much hope in this plan drawn up by the tech investor Matthew Clifford? Part of the answer lies in productivity: the term for how much output a worker can produce in a hour. The International Monetary Fund has predicted that AI will increase UK productivity by up to 1.5% a year.
Low productivity has bedevilled the UK for years, partly due to low investment in nifty technology. AI, it is hoped, will help British workers produce more, which should raise wages and allow spare capital – you don’t need so many workers to do a certain job – to be invested elsewhere. This is even more important if, with an ageing population, the UK must cope with fewer working-age adults in the future.
“If we see the working-age population shrinking you need to see productivity increase dramatically in order to see any sort of economic growth,” says James Knightley, chief international economist at the banking group ING.
This logic also applies to the public sector, with the plan calling on state bodies to pilot AI services.
Underneath all of this is the implication that efficiency – through AI automating certain tasks – means redundancies. The Tony Blair Institute (TBI) has suggested that more than 40% of tasks performed by public sector workers could be automated partly by AI and the government could bank those efficiency gains by “reducing the size of the public-sector workforce accordingly”.
TBI also estimates that AI could displace between 1m and 3m private-sector jobs in the UK, though it stresses the net rise in unemployment will be in the low hundreds of thousands because the technology will create new jobs, too. Worried lawyers, finance professionals, coders, graphic designers and copywriters – a handful of sectors that might be affected – will have to take that on faith. This is the flipside of improved productivity.
But ensuring that the UK plays a key role in developing a transformative technology and deploying it properly across the private and public sectors requires a coordinated industrial strategy. Long-term industrial plans are complex beasts and require cooperation across multiple fields – from skills to energy infrastructure and regulatory frameworks – hence the 50 recommendations from the report that the government is committed to putting in place. They include setting up “AI growth zones” with fast-track planning privileges, launching a body to support leading domestic AI firms and improving AI-related work skills.
There are also elements of the government’s AI policy that will raise concerns. The plan’s proposal to create national datasets composed of public data will have to jump hurdles related to privacy, ethics and data protection, while a move last month to allow AI firms to train their models on copyrighted work was rejected by the creative industries and publishers.
But for Starmer and Reeves, growth is key.
Dame Wendy Hall, a professor of computer science at the University of Southampton and a member of the UN’s advisory body on AI, says it is “imperative” for the economy that the government makes the plan work.
“It’s not a question of ‘can they deliver it.’ They have to deliver it.”