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Skilled roles least threatened by automation, says ONS

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Nicholas Fearn

Around 1.5m jobs will be affected by automation over the next few years, according to new research from Office of National Statistics in the UK.

ONS analysed 20 million workers in 2017 and found that 7% were at high risk of automation. The proportion of jobs at low and medium risk of automation is growing, possibly because “automation of some jobs has already happened”, said the ONS. “For instance, self-checkouts at supermarkets are now a common sight, reducing the need to have as many employees working at checkouts.

“Additionally, while the overall number of jobs has increased, the majority of these are in occupations that are at low or medium risk, suggesting that the labour market may be changing to jobs that require more complex and less routine skills.”

The top three roles at high risk of automation were waiters and waitresses, shelf stackers and basket collectors, all of which tend to be low skilled and routine.

Roles facing least risk of automation were highly skilled specialists such as medical practitioners and higher education teachers.

ONS also found that job descriptions with the words “machine”, “equipment,”, “clean and  “operate” were at high risk of automation, while low-risk jobs were likely to contain “plan”, “research, “patient” and “treatment”.

The ONS methodology groups probabilities of automation in three categories: low risk of automation for probabilities lower than 30%, medium when the probability falls between 30% and 70%, and high risk if the probability is greater than 70%.

Women hold 70% of roles at high risk of automation, and 15% of young people aged between 20 to 24 years old are employed in jobs that are highly likely to be automated one day.

“It is not so much that robots are taking over, but that routine and repetitive tasks can be carried out more quickly and efficiently by an algorithm written by a human, or a machine designed for one specific function,” said ONS. “The risk of automation tends to be higher for lower-skilled roles for this reason.”

Impact on property

When it comes to the impact of automation in the real estate sector, 31% of property, housing and real estate management roles are at some risk of automation, but not all of it high.

Low-risk property roles include architects (22%), chartered architectural technologists (27%), chartered surveyors (25%), construction project managers (26%) and town planning officers (23%), all of which require high skill and experience.

In comparison, manual property roles are far more likely to be automated – including bricklayers (54%), construction operatives (59%) and electricians (51%).

Dan Hughes, CEO of LIQUID Real Estate Innovation, said there is no question that technology will have a significant impact on real estate jobs in the future.

He told PlaceTech: “However it will not so much be whole jobs that are automated, but specific tasks within wider roles. This will mean that today’s real estate jobs will be different in the future with an increased emphasis on the human skills such as ethics or advice.”

Mike Price, Director at MPA Group, said: “The process of automating factories began a long time ago, but in recent years the technology has developed to such a level that it is becoming ubiquitous in industry.

“It’s only natural that companies will incorporate it into their business models, as if deployed smartly, automated machines can both improve existing supply chains and provide new opportunities.”

But Price admitted that there are drawbacks, primarily to do with people and logistics. He added: “Incorporating these new technologies into a supply chain can come at a hefty cost and can require major redevelopment of business models.

“There’s also the obvious and much-discussed danger of automation replacing jobs. The fear that technology will replace humans in workplaces has been around for a long time and while automation does have the potential to take over some processes within supply chains, in the foreseeable future it’s unlikely to completely render existing workers redundant.”

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