Automatic for the people?

Response to Jeremy Corbyn's party conference speech

Author: Liam Booth-Smith   |   27/09/2017

In response to today’s conference speech by leader of the Labour Party Jeremy Corbyn, in which he will call for the establishment of a National Education Service, Localis chief executive Liam Booth-Smith writes:

Jeremy Corbyn has hit upon the right diagnosis in automation, but has fluffed his policy response to the problem. The creation of a National Education Service is the wrong answer to the question posed by industrial and technology-driven change. Top-down solutions should not be automatic for the people.

Localis research has helped further identify those areas of the country most at risk from automation (see table below), and the difference between those prosperous local economies well-poised to make the leap and more disadvantaged regions, likely to experience industrial failure, is huge. In around half the areas of the country we don’t need a top-down, centrally-imposed skills service but require more local solutions attuned to business needs.  There is no time to lose, so why waste time and squander resources for reskilling local labour markets appropriately?

In our view, there is a crucial role for places, empowered by Westminster, to play in easing this transition and helping the current occupants of these jobs stay active and equipped in the labour market. Our forthcoming report will argue for a smoothing in the transition, not just in the automation of manual jobs but also in the labour shortfall some areas will face with the introduction of national-level immigration controls in the wake of the UK’s exit from the European Union.

The places most at risk of automation

Localis has produced a scorecard ranking 47 strategic authority areas of the country most at risk from the automation of jobs (see below) in which Brighton and Hove is best-placed to cope with change and Northamptonshire most at risk.

The ‘automation score’ is the amount of the area’s total employment taken up by the sectors identified by PwC as being most likely to see a large increase in automation by 2030. The lower the score, the lower the area’s exposure to automation risk. We take the number of local jobs in these sectors and – using the percentage of jobs within the sector identified as ‘high risk’ – produce an overall percentage of the area’s jobs which are at high risk of being automated.  We index these statistics with the average being 100 to create a simple score for an area’s risk exposure.