Third of jobs are at risk from automation – with towns in the North and Midlands most endangered
A new map reveals the scale of the threat posed by artificial intelligence, showing shadow chancellor John McDonnell's constituency is most likely to feel the effects
A NEW MAP has revealed a third of jobs are at risk from automation with towns in the North and Midlands most endangered.
It comes from a report by a think tank which reveals the scale of the threat posed by robots - with workers in John McDonnell's constituency most likely to feel the effects.
But polling done alongside the research shows just 7 per cent of Brits are worried about being made redundant by robots.
, who produced the report on the impact of AI in UK constituencies, said: “Our findings are startling.”
“The proportion of jobs at high risk of automation by the early 2030s varies from 22 per cent to 39 per cent for different constituencies.”
It said the rise of robots could lead to “unprecedented” change, and says the ex-industrial heartlands in the North and the Midlands are most likely to lose their jobs.
The study says upheaval could make the industrial revolution pale in comparison, and slams the government for failing to prepare for the upcoming changes to employment.
In a withering indictment it concludes: “So far no party has anything like an adequate policy response to maximising the opportunities and minimising the risks that lie ahead.”
It adds: “Our analysis now suggests that the unequal geographical distribution of the impact of automation deserves immediate attention by Government, particularly as it is regions that have previously suffered the effects of industrial decline that are likely to be worst hit.”
It also warned technological change had the potential to cause political upheaval, and its influence can already be seen in the Brexit vote and Donald Trump's election.
But it said public attitudes also need shifting, with polling showing “despite evidence suggesting high levels of automation are coming, the majority of people remain unworried about the impact of automation on their jobs and on jobs in their local area”.
The research predicts Shadow Chancellor Mr McDonnell’s constituency of Hayes and Harlington will see the highest rates of automation, with almost 40 per cent at high risk of going by the early 2030s.
This is mainly due to the fact many workers are employed around Heathrow, and the report suggests a large proportion of jobs in the “transportation and storage” industry set to become automated.
In fact all five of the constituencies most vulnerable to AI are characterised by high numbers of jobs in this or the manufacturing sector.
On the flip side the constituency least at risk is Edinburgh South, as the city has a larger proportion of high-skilled occupations than most places – jobs which are much less likely to go to robots.
Five constituencies most at risk of automation:
- Hayes and Harlington
- Crawley, Sussex
- North Warwickshire
- Alyn and Deeside, Wales
- Brentford and Isleworth
Five constituencies least at risk of automation:
- Edinburgh South
- Glasgow North
- Liverpool West Derby
- Oxford East
- Wirral West
Plan to soften the blow of the rise in automated jobs
Future Advocacy is making several recommendations to the UK Government:
- Commission and support further detailed research to assess which employees are most at risk of job displacement by automation
- Develop smart, targeted strategies to address future job displacement, based on the results of research into the differential impact of automation by sector, region and demographic group in the UK.
- Draft a White Paper on adapting the education system to maximise the opportunities and minimise the risks created by AI.
- Make the AI opportunity a central pillar of the UK’s Industrial strategy and of the trade deals that the UK must negotiate post-Brexit.
- Ensure that the migration policy in place following Brexit will still allow UK-based companies and universities to attract the brightest and best AI and robotics talent from all over the world.
- Conduct research into alternative income and taxation models that result in fairer distribution of the wealth that these technologies will create.
