March 26, 2019
Automation could replace 1.5 million UK jobs, according to Government study
Around 1.5 million jobs in England are at high risk of some of their duties and tasks being automated in the future, Office for National Statistics (ONS) analysis shows. The ONS has analysed the jobs of 20 million people in England in 2017, and has found that 7.4 percent are at high risk of automation. Women, young people, and those who work part-time are most likely to work in roles that are at high risk of automation.
The ONS study defines automation as involving replacing tasks currently done by workers with technology, which could include computer programs, algorithms, or even robots.
The proportion of jobs at a high risk of automation decreased slightly between 2011 and 2017, from 8.1 percent to 7.4 percent, while the proportion of jobs at low and medium risk of automation has risen.
The exact reasons for the decrease in the proportion of roles at high risk of automation are unclear, according to the study, but it is reasonable to conclude that automation of some jobs has already happened. 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.
[perfectpullquote align=”right” bordertop=”false” cite=”” link=”” color=”” class=”” size=””]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[/perfectpullquote]
The analysis looked at the tasks performed by people in jobs across the whole labour market, to assess the probability that some of these tasks could be replaced through automation. 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. The risk of automation tends to be higher for lower-skilled roles for this reason.
When considering the overall risk of automation, the three occupations with the highest probability of automation are waiters and waitresses, shelf fillers and elementary sales occupations, all of which are low skilled or routine. The three occupations at the lowest risk of automation are medical practitioners, higher education teaching professionals, and senior professionals of educational establishments. These occupations are all considered high skilled.
The ONS has launched a chatbot for people to use to get more information about their own role.
The role of age and gender
The ONS analysis shows that 70.2 percent of the roles at high risk of automation are currently held by women. In addition, people aged 20 to 24 years are most likely to be at risk of having their job automated, when compared with other age groups.
Younger people are more likely to be in roles affected by job automation. Of those aged 20 to 24 years who are employed, 15.7 percent were in jobs at high risk of automation. The risk of job automation decreases for older workers, and is lowest for workers aged between 35 and 39 years. Just 1.3 percent of people in this age bracket are in roles at high risk of automation. The risk then increases from the age group 40 to 44 upwards.
This pattern can be explained by the fact that workers naturally obtain further skills and become more knowledgeable in their field as they progress further in their careers. When young workers enter the labour market, they may be entering part-time roles and employed in industries like sales, retail, and other roles where some degree of automation is highly likely. Many young workers may move through a range of roles before settling into a career. In addition, younger workers have more time and opportunity to retrain or change career paths.
We can partially explain the increase in the risk of automation from the age of 35 years with the change in working patterns, particularly for women. From the age of 30 years, more women work part-time, and this increases until women reach the age of 50 years, when it then steadily drops down. People who work part-time are more likely to work in roles at a higher risk of automation, but ultimately your occupation determines the probability of automation, not your working patter, the report concludes.
