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Canada’s small towns face the highest risk of losing jobs to automation, government analysis shows

Rural and small-town Canada risk falling even further behind the country’s booming cities as technology takes over routine tasks from human workers, according to a federal government analysis obtained by The Logic.

Communities like Brooks, Alta. and Lachute, Que., where many residents work manufacturing, transport or natural resources jobs, are most vulnerable to automation, the analysis found, while large urban centres like Ottawa and Fredericton are insulated by their large numbers of government and education jobs.

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Canada’s small towns face the highest risk of losing jobs to automation, government analysis shows

By Murad Hemmadi
A miner walks past the conveyor system of a continuous boring machine near an active mining wall at the Nutrien Cory potash mine in Saskatoon on Aug. 12, 2019. Photo: James MacDonald/Bloomberg
Dec 26, 2019
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Rural and small-town Canada risk falling even further behind the country’s booming cities as technology takes over routine tasks from human workers, according to a federal government analysis obtained by The Logic.

Communities like Brooks, Alta. and Lachute, Que., where many residents work manufacturing, transport or natural resources jobs, are most vulnerable to automation, the analysis found, while large urban centres like Ottawa and Fredericton are insulated by their large numbers of government and education jobs.

Talking Point

Urban centres will see most of the growth from technological disruption, while rural areas and small towns fall further behind as machines replace workers, according to documents prepared for a June 2018 meeting of senior federal officials. An internal government analysis shows regional economies dependent on sectors like manufacturing and mining are most susceptible to automation, while capitals and diversified cities are less affected. 

“Regional economies dependent on high-risk sectors like manufacturing or mining, such as southwestern [Ontario] and northern [Alberta], will likely see more disruption,” states a presentation prepared for a June 2018 meeting of deputy ministers from key departments like finance, innovation and employment. “Communities with a large hospital, post-secondary institution or public sector presence, such as Ottawa-Gatineau, are less susceptible to automation.” 

The document identifies the communities in each province with the largest and smallest share of workers at high risk of being affected by automation. The Logic obtained it via access-to-information request, then received an updated version of the analysis from the finance department. 

More than a fifth of workers are considered high risk in each of the nine vulnerable towns and cities identified. (Finance Canada does not identify a specific highest-risk community in New Brunswick, instead listing the province’s rural areas as a whole. The analysis also does not extend to Yukon, Nunavut or the Northwest Territories.) All have populations under 35,000; in seven, a larger share of the labour force is employed in manufacturing jobs than in their respective provinces and the country as a whole. 

In the two exceptions—Bay Roberts, Nfld. and Lloydminster, Sask.—more than a quarter of workers are employed in high-risk natural resources or trades occupations. “The most susceptible are much more homogenous labor markets focused on either a single industry or a single employer within an industry where more of the job tasks in that industry [could be automated],” said Creig Lamb, a senior policy analyst at the Brookfield Institute for Innovation & Entrepreneurship, on whose work the government’s regional analysis is based.

Read more:

 

  • Catherine McIntyre travelled to Brooks, Alta. to find out how Canada’s most vulnerable city is preparing for its robotic future.

 

  • See which cities in each province are most and least likely to be impacted by technological disruption

Small towns and rural regions may also have less educated workforces than urban centres, so they’re “less likely to seize the economic opportunities presented by new technologies,” the presentation states. And they’re less able to cope with shocks, whether they’re caused by automation, outsourcing or an economic downturn. “Say you’re up in Fort [McMurray]. If you get laid off [by] the one employer out there, there’s no other jobs, so you’re out of luck,” said Lamb. “In a much more deep, diverse labor market like Toronto, [there’s more] ability to absorb the extra labor and have them find jobs elsewhere.”

The lowest-risk places identified by the finance department are indeed larger—four are the most populous cities in their respective provinces, while another three are in the top three. Many are government towns, including the capitals of the four Atlantic provinces, Saskatchewan and Manitoba, as well as Ottawa and Gatineau, where many federal departments and public servants are based. 

According to Lamb, many of Canada’s medium and large cities house a similar list of occupations, including health care, sales and service and education. “The things that aren’t automatable are [those] that humans uniquely do,” he said, such as interacting with other people, creativity, problem-solving and management. The presentation notes that occupations involving cognitive or difficult-to-automate manual tasks, like consultants or personal support aides, have seen stronger wage and employment growth than routine workers, like clerical staff.

Out west, two small towns buck the big-city trend, thanks to a large number of such jobs. Canmore, Alta.—population 13,992 as of the 2016 census—is the province’s lowest-risk community. The municipality promotes itself as a tourist destination; nearly 15 per cent of its labour force is employed in the accommodation and food services industry, more than twice the national rate. And in British Columbia’s interior, the slightly larger Nelson is home to Kootenay Lake Hospital, and nearly 1,000 health-care workers. 

Across the country, 17.5 per cent of workers are at high risk of being affected by automation, according to the finance department’s analysis. But the calculations don’t take into account new jobs created by innovation, so there won’t necessarily be fewer jobs in the future, said department spokesperson Anna Arneson. She called the estimates “highly uncertain,” and said they don’t represent “definitive conclusions about particular cities or towns,” but instead demonstrate the variation across regions of high-risk occupations.   

Methodology

In a 2016 paper, Creig Lamb, a senior policy analyst at the Brookfield Institute for Innovation & Entrepreneurship, applied global consultancy firm McKinsey’s methodology to Canada’s National Occupation Classification system, to identify the proportion of an occupation’s tasks that can be automated. Finance Canada used Lamb’s list of jobs along with Statistics Canada’s 2016 census data to determine the percentage of workers in communities in each province that are at high risk of being affected by automation. An occupation was defined as being at high risk if more than 70 per cent of its tasks could be automated with current technology. Finance Canada used data at the census metropolitan area or census agglomeration level, which measure neighbouring areas around a core with populations of at least 100,000 and 10,000 people, respectively.

Lamb also cautioned that while technology has the potential to take over some tasks and a large share of certain jobs, there’s no guarantee that will happen. “The firm has to decide that it wants to automate,” he said, citing possible obstacles like the costs of implementation, the need to train employees on new systems and regulatory barriers. Canadian companies also lag behind their peers in other large markets on technology adoption—the country ranks 16th out of 32 on an OECD ranking of investment in information and communications technology.  

Even when automation does occur, “it’s not always a case of one widget of technology replacing one worker,” Lamb said. Instead, new machinery and systems often make firms more productive, causing them to staff up. New companies and industries also develop around new technology. Policymakers should be pushing Canadian firms to adopt more innovation, not less, to ensure they remain competitive, according to Lamb.

When automation causes layoffs or company closures, Lamb said municipal governments should “work with all the other employers to identify where they need talent,” and with local colleges to help displaced workers get the skills for those jobs. As an example, he cited North Carolina, which has lost much of its textile industry but launched a biotechnology training program to fill roles in that growing sector in 2004.

In the future, workers will need to “constantly re-skill or up-skill to be successful,” the presentation states. It warns that “Canada’s policy suite to help displaced workers and promote lifelong learning appears to be less pro-active” than other countries; Canada is below the OECD average in both government spending on training and the share of the labour force that takes part in such programs. 

Governments, businesses and educational institutions must coordinate to ensure that skill development is accessible and adapts to changing employment needs, and labour rules should be adapted to protect workers rather than jobs, according to the presentation. It also suggests promoting a culture of lifelong learning and encouraging early development of “cognitive, social and behavioural skills that improve adaptability.”

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Employment Minister Carla Qualtrough did not directly answer The Logic’s questions about the risks of automation in rural areas and small towns. The government has programs “to keep Canada’s labour market competitive and help Canadians acquire the skills they need to find and keep good jobs, recognizing that workforce needs and opportunities are not the same in all regions,” said spokesperson Veronique Simard, citing among others Skills Boost, which provides financial support to workers who return to school after losing their jobs; the upcoming Canada Training Benefit, a tax credit for continuing education; and funding to the provinces via labour market and workforce development agreements.

“There need to be more efforts focused on helping [mid-career] workers transition from areas of the economy that are shrinking to ones that are more resilient,” Lamb said.

#automation

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