Job losses through automation: Australia’s top 10 most and least vulnerable regions

job losses automation

Mount Gambier. Source: Wikimedia Commons.

Jobs in regional cities are likely to be most heavily impacted by automation, while metropolitan areas appear least vulnerable, according to research by the Regional Australia Institute.

Just how many job losses automation will cause in coming decades is a difficult thing to predict, but a new tool aims to help local leaders prepare.

There have been estimates 44% of jobs across Australia are highly vulnerable to automation, though the latest research by the Regional Australia Institute suggests it could be more like 26%.

“By 2030, employers will place greater demand on skills that are high tech (i.e. specialist), high touch (i.e. practical), and high care (i.e. personal),” says the institute.

Some communities will be hit harder than others — regional cities often provide support services to metropolitan areas and have a higher proportion of the types of job likely to be automated, such as in retail, clerical and admin, factories and hospitality. There is a silver lining, however, as regional cities also tend to do reasonably well on innovation, with a high number of new businesses and trademarks.

Metropolitan areas, on the other hand, “often have the highest concentration of professionals (e.g. medical, legal, and education), managers, and community and personal service workers (e.g. childcare or health and welfare support),” says the institute.

“Because of the existing occupation makeup and technological readiness and connectivity of metropolitan areas, they seem less likely to be impacted by the increasing automation of work than other regional types.”

The Regional Australia Institute has released a job vulnerability data tool, allowing users to break down information by local government area, as well as a background paper and a list of occupations most vulnerable.

They hope this will “provide local leaders and decision makers with the information they need to identify key problem areas and start developing responses to maximise opportunities and minimise, or eliminate, potential barriers.”

Top 10 most and least vulnerable

The 10 local government areas with the highest proportion of jobs highly vulnerable to automation are mostly regional cities or on the suburban edge. Four are in South Australia.

  1. Mount Gambier, SA (33%)
  2. Gawler, SA (33%)
  3. Sorell, Tas (32%)
  4. Griffith, NSW (32%)
  5. Warrnambool, Vic (32%)
  6. Albury, NSW (32%)
  7. Victor Harbor, SA (32%)
  8. Shellharbour, NSW (32%)
  9. Tea Tree Gully, SA (32%)
  10. Moonee Valley, Vic (32%)

Mount Gambier is “an industry and service hub that has a diverse economy but a large number of clerical and administrative workers (i.e. people jobs susceptible to automation),” says the report.

Two of the highest vulnerability local government areas are metropolitan: Tea Tree Gully and Moonee Valley. “In both of these LGAs, the largest employer is retail trade, with many people working as sales assistants and salespersons, both jobs that are highly susceptible to automation.” Perhaps the impact on people living in these suburban areas is not as strong as in a regional city, however, given the presumably higher proportion of people who commute elsewhere for work.

The Regional Australia Institute counsels that it’s not all doom and gloom. Apart from Griffith and Sorell, even in the list of areas with the most vulnerable jobs, there are still a greater number of low vulnerability jobs.

It’s not surprising, on the other hand, that the 10 council areas with the highest proportion of low vulnerability jobs are all reasonably prosperous metropolitan areas:

  1. North Sydney, NSW (66%)
  2. Nedlands, WA (61%)
  3. Subiaco, WA (60%)
  4. Sydney, NSW (59%)
  5. Ryde, NSW (59%)
  6. Canberra, ACT (58%)
  7. Melbourne, Vic (58%)
  8. Lane Cove, NSW (58%)
  9. Yarra, Vic (57%)
  10. Port Phillip, Vic (57%)

The institute also notes that rural areas — which it calls ‘heartland regions’ — have the smallest proportion of jobs vulnerable to automation, but that poor mobile and internet connectivity will hinder growth in digital jobs and make it difficult to adapt to change.

The article was originally published on The Mandarin. Read the original article.

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