How is risk distributed throughout Canada?
By mapping McKinsey statistics to the latest Canadian data (National Household Survey 2011), we were able to identify the concentration of work with the potential to be automated for all Canadian Census Metropolitan Areas (CMAs) and Census Agglomerations (CAs). The data shows that risks associated with automation will be unevenly distributed across Canada. Many CMAs and CAs specializing in manufacturing or resource extraction are most at risk. These towns and cities are found primarily in Saskatchewan and Alberta, as well as southwestern Ontario and southern Quebec.
For example, almost one-quarter of the labour force in Ingersoll, a small town in southwestern Ontario, is employed in the manufacturing industry. This town has already felt the brunt of some of the trends associated with the decline in manufacturing in the province. In January 2017, General Motors announced that it is cutting 625 jobs from its assembly plant in the area and moving them to Mexico. As recent studies from the United States have shown, both automation and globalization have taken a significant toll on manufacturing employment since the 1990s, particularly for routine assembly line jobs requiring less than a post-secondary education.
The Regional Municipality of Wood Buffalo is another example. This municipality occupies a significant land mass in northeastern Alberta and is home to both Fort McMurray and a large portion of the Athabasca Oil Sands. Wood Buffalo, where 30 percent of total employment is concentrated in oil and other extractive industries, was hit particularly hard by the recent oil shock. However, even as the price of oil rebounds, many now fear labour saving technologies will result in a leaner, more technologically-driven oil industry—preventing a return to pre-shock job numbers in these regions.
Even Canada’s largest cities are not immune to the effects of automation. In the country’s three largest CMAs—Toronto, Montreal, and Vancouver—the potential for automation is equivalent to nearly 2.7 million jobs.
On the other hand, Canada is also home to a diverse array of towns and cities with a high concentration of industries relatively insulated from the effects of automation. These include many smaller cities and towns with either a large hospital presence such as Corner Brook, Nfld., home to the largest regional hospital in the west of the province, or post-secondary institutions, such as Kingston, Ont., home to Queen’s University. It also includes, to a lesser extent, some of Canada’s larger cities, which have diverse economies that employ people across the skill spectrum. However, technology now has the capacity to automate work activities across all industries. Therefore, cities and towns across Canada may feel its impacts, regardless of their industrial composition.
However, the increasing capacity of technology combined with the fact that many of Canada’s cities and towns have a similar distribution of employment across industries, means that automation has the potential to impact a significant portion of the labour force in cities and towns across Canada.
What does this mean for the future of work?
The potential to automate a task does not necessarily mean that it will be automated. Considerations such as cost and cultural preference may argue in favour of labour. The diversity of a local economy will also determine the potential impact of automation on a given city or town. For example, a highly specialized city with a significant proportion of work with the potential for automation is likely more vulnerable to these technological trends compared to a similar city with a more diverse economy.
In cases where technology adoption does displace workers, it is possible that some jobs will be changed rather than lost, or that new jobs will be created, likely with different skill requirements. Take for example, prominent U.S. investment bank Goldman Sachs, which at its peak employed over 600 stock traders. Today, thanks to machine-learning algorithms capable of making complex trades, these 600 traders have been reduced to just two. However, technological developments also increased demand for other jobs and skills in the company. About one-third of Goldman Sach’s staff—roughly 9,000 people—are now employed as computer engineers.
In fact, technological progress has been one of the most significant drivers of productivity and long-term economic growth in Canada. As Canada’s population ages and the future of many of our resource extractive industries becomes increasingly uncertain, technologically-driven innovation will arguably become even more important to secure future economic growth.
However, the impact on cities and towns that are more susceptible to automation is less clear. Technology is rapidly encroaching on a whole new set of job tasks, increasing the risk of automation for a large number of jobs outside the realm of what was once technically feasible, ranging from truck drivers to law clerks.
The uneven distribution of this risk should not be understated. Canadians will experience the impacts of automation differently, depending on the community they live in, the industry they work in, and their education and skill levels, as well as their income level and demographic characteristics. It will be important for policymakers to understand who is likely to be hit harder by technological change, in order to design policies and programs that will help to mitigate these negative impacts.