Richard Brown: What will generative artificial intelligence do to London?

Richard Brown: What will generative artificial intelligence do to London?

Since their earliest days technology has shaped cities. The industrial revolution founded the great manufacturing centres of the 19th Century; trains fuelled London’s growth, replacing market gardens with metro-land; and global information and communication technology networks founded a network of global cities in the late 20th Century.

Right now, social media are clamorous with hype about artificial intelligence (AI), and the pace of change seems dizzying. Anyone who has played with “generative” AI tools such as OpenAI’s ChatGPT, Google’s Bard, or Midjourney’s image generators will have experienced the uneasy feeling that they are dealing with something sentient, however much they know that these systems merely aggregate and recombine information.

What impact is this wave of innovation likely to have in London, and on London’s economy in particular? In recent weeks, a few academic and commercial studies considering the labour market impact of generative AI have been published. This article tries to weave together some of their threads.

One piece of positive news is that London is the leading European city for AI. A 2021 survey by the government’s Digital Catapult identified the UK as the third most important centre for it after the USA and China, with more than 70 per cent of UK AI firms and – judging by 2020 job postings – around a third of all new advertised AI jobs based in London.

London’s tech sector has grown fast and is estimated to employ around 900,000 people. But the impact of generative AI is likely to extend beyond the capital’s silicon centres and suburbs. One team of researchers, Tyna Eloundou and colleagues, have looked at detailed task descriptions for US occupations to estimate the impact that generative AI technologies could have. Overall, they estimate that 80 per cent of the USA workforce could be affected by them, with around 20 per cent being heavily affected. The impact would be greatest for higher paid jobs and those held by graduates.

The research team has not published details of its analysis, but does summarise the impact on different industries. At the top of the list, with more than 40 per cent of tasks affected, are various financial services and IT subsectors, as well as a publishing and broadcasting (non-internet), and professional, technical and scientific services.

A Goldman Sachs report reaches similar conclusions. It argues that the impact of generative AI will be greatest in advanced western and far eastern economies. In Europe, it suggests the greatest impact will be on professionals, associate professionals, clerical support workers and managers, with legal service and office administration likely to be affected most heavily.

These findings map pretty squarely onto the three categories of professional services which dominate the London economy: information and communications; finance and insurance; and professional, scientific and technical services. These sectors have grown in importance in the capital. They made up 31 per cent of jobs in London in 2022 compared to 27 per cent in 2012. They are also concentrated in the capital, accounting for almost twice the proportion of jobs as across the UK as a whole.

Saying that these “knowledge economy” sectors are those most exposed to the impact of generative AI is more or less the precise opposite to what Centre for London colleagues and I found five years ago in our report on disruption to the capital’s labour market. Based on an analysis of how “automatable” different occupations were, we argued that London’s information and communications and its professional, scientific and technical services had the lowest automation potential (finance and insurance was slightly higher).

Why the difference? Were we wrong? Are these new analyses wrong? What has changed? Without re-running our analysis, I suspect part of the difference lies in occupational mix. Many London workers undertake more specialised and knowledge intensive tasks within particular industries. Underwriting risk at Lloyds of London is very different from working in a claims call centre.

But I think our expectations have shifted too. Generative AI is a qualitative change. When we wrote the Centre for London report, we were generally talking about the scope for specialised algorithms to automate specific routine tasks. These new technologies go further: they can draw on huge databases to generate new content. They can respond to simple user requests, writing and refining algorithms on demand. They can draft summaries, presentations, poems and speeches. They are creating visualisations. They are even being deployed in therapy. This is extending their reach much further into professional services than we envisaged.

Will this change destroy jobs? The traditional response is to say, “No! Every other technology has created jobs. This will too.” I think that is certainly right in the short term. The measure of impact used by the Eloundou study is whether generative AI could theoretically speed up tasks by more than half. A recent empirical study found that AI-enabled workers took an average of a third less time to complete certain standardised tasks and produced a better graded submission at the end. Workers also expressed more job satisfaction, spending more time coming up with ideas and editing, and less time drafting.

This sounds like a potential boost to productivity for London’s service sectors – one the capital and country urgently need. Productivity gains can, of course, be realised by cuts in wage bills, but that is only part of the story. AI may also unleash supply of and demand for new products and services. Economics blogger Noah Smith has compared its impact to that of machine tools, which displaced craft manufacture but led to ever increasing demand for goods and employment in manufacturing – at least for a century or so.

London is perfectly positioned to catch this wave of opportunity, creating new software to meet new demands and launching a new wave of hybrid services, following in the path of fintech and medtech. But the impact may go deeper still. Eloundou and colleagues argue that generative AI is already showing signs of being a “general purpose technology” like printing or steam engines, characterised by “widespread proliferation, continuous improvement, and the generation of complementary innovations”. If that is the case, AI will change our world in ways that we cannot yet comprehend.

All this is wildly speculative. At the extremes, London could be left unaffected by AI, though I fear that would be the stagnation option. Or AI may destroy humanity, making predictions moot. Between these poles, job destruction is by no means certain and if AI allows more leisure time alongside more equitably shared prosperity, that might not be a bad thing. But disruption probably is. London could be in for an exciting but choppy few years.

The editor accepts no responsibility for the choice of image. Follow Richard Brown on Twitter.

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Categories: Analysis

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