Nesta’s Hasan Bakhshi and Eddie Copeland examine the impact on the UK public sector workforce of a range of global trends
In recent years, the public’s fascination with AI and robots has kept think tanks and consultants busy.
However, in Nesta’s new research for Pearson, The Future of Skills: Employment in 2030, we show that a single-minded focus on automation misses the bigger picture in important ways.
In particular, long-run trends like population aging, urbanisation and technological change in all its forms – say, biotechnology, the materials revolution and the Internet of Things, as well as automation – will have profound implications for employment in the future. A focus on automation to the exclusion of these other trends risks distorting our understanding of the different workforce challenges and opportunities that lie ahead and of how we should respond to them.
In some cases, the trends reinforce one another; in others, they offset in ways which are missed when viewed in isolation. Nowhere is this more apparent than in public-sector occupations, which our analysis predicts will see strong growth in the long term.
Our research approach starts from three key facts.
First, that – despite disruptive technological and industrial change – there is a high degree of persistence in the composition of the workforce, suggesting that looking back at the history of employment is a good starting point for making predictions about its future.
Second, the US and UK economies are experiencing multiple breaks in long-run trends that should be expected to have major consequences for employment. The implication is that naïve extrapolation paints an incomplete and potentially biased picture of future prospects.
And third, occupations are complex. They deploy a complicated mix of knowledge, skills and abilities, and are performed using a variety of activities and tasks, meaning that the models we use to generate quantitative labour market predictions must be sophisticated.
Reflecting these facts, our research comprises three stages: in stage one, we review and synthesise in the form of a deck what the literature says about long-run trends impacting on the labour market. In stage two, we present this to experts at foresight workshops to debate the implications of structural breaks in the trends for future employment. During these workshops, we also ask the experts to label a set of 30 occupations according to whether they expect them to rise or fall in demand by 2030. In the third stage, we use these expert-assigned labels to train a machine learning classifier of whether an occupation will become more or less important in the future, exploiting rich data on the job requirements of different occupations provided by the US Department of Labor.
We refer readers to our report and data visualisations for our full set of findings, but a striking feature is the strong predicted growth in demand for education, health and personal care occupations. This reflects trends such as population aging and changing consumer preferences towards healthcare and lifelong learning, as well as the fact that people-focused services tend inherently to have lower productivity growth.
Prevention and cure
To those observing the impact of recent austerity measures in the UK, this future outlook may come as a surprise: the dominant public sector trend since 2010 has been to reduce headcount. However, our research suggests that, in the longer term, such pressures will hit up against growing demands for public services.
Seen in this light, the activities of public sector professionals working in these fields are likely to be augmented, not replaced, by technology. Already, artificial intelligence is being used to help social workers, healthcare professionals and teachers. And the ability to apply predictive modelling to public sector data may enable a shift from the traditional model of public service provision, which addresses failure after it happens, to one that focuses on (more human capital-intensive) prevention.
While, no doubt, there will be further pressures in the public sector to reduce employment, all the evidence from our research is that the demand for the services of public-sector professionals is not going away any time soon.