One of the many, many frustrating things about Canadian policy over the past couple of decades is the combination of blindness and bad habits that our policy makers have with respect to the role of skills.
Let’s start with the blindness, which mostly applies to our policymakers’ understanding of the relationship between skills and innovation. Innovation, to be clear, is not “invention”. It’s not about discovering some new idea or application and then building a world-beating company around. This might be the tech bro understanding of what innovation is, it definitely seems to be what the Canadian Council of Innovators seems to believe it is, and too often it seems to be the Government of Canada’s understanding as well. But. It. Is. Wrong. Innovation is the general application of new ideas to all processes across the economy as a means to bring about not just novelty but greater efficiency and value as well.
To achieve this economy-wide, you need three things. You need new ideas. You need people who can turn new ideas into specific products and services. And you need people who understand how to put these products and services to use in their own businesses in order to become more productive. Governments can address this through various types of programs which focus on research and development. We can debate a bit about how well Canada’s programs work, but that part we have covered. The last part – having the skills to actually use new products and services – is almost completely ignored here.
(If you want more on the role that both research policies and skill policies can impact innovation and growth, I would recommend reading Darius Ornston’s When Small States Make Big Leaps: Institutional Innovation and High-Tech Competition in Western Countries. The contrast between policies adopted taken in Denmark and Finland is instructive).
You can see this most clearly in the way we approach Artificial Intelligence. Canada has put a lot of money into research on artificial intelligence (Mila, Vector, Amii, etc). We have put a fair bit of time and effort into commercialization of AI and boosting the companies turning AI into products. But all of this is mostly irrelevant if Canada does not have a workforce that is able to work out how to apply AI to actual business cases. You would need mass AI literacy, millions of workers who understand how to use AI in non-slop ways, to turn put new technology into useful, productive ends.
You will be shocked, dear reader, to find out that while Canada’s AI strategy still nods to research and commercialization, but pays no attention to the skill set of workers and managers across the economy. To the extent the word “skills” is used, it is entirely with respect to people who can develop and program AI models, not to people who will actually put them to use in citizen or client-facing modes. It’s a last-mile problem of enormous magnitude and simply no one seems to be paying attention.
But that’s not the only problem with our skills discourse. The other one is the way that skills “shortages” (itself an under-problematized term) always turns into an education problem in that can only ever be solved by producing MORE graduates in field X. These days it’s “sustainable jobs” or “net zero” jobs, but it could just as well be health jobs or – until the last few months at least – coding jobs: the solution is always MORE.
When Canada’s working-age population was expanding, MORE was a reasonable strategy. It also has the benefit of being a strategy which is easier to understand, and also of being both easy and financially advantageous for educational institutions to adopt. But when growth is basically zero, trying to move workers over into a “hot” job field just creates shortages elsewhere. Eventually it just becomes whack-a-mole.
There is an alternative. Instead of MORE, why not “better”? Instead of focusing on the number of graduates we are producing in a given field, why not put the emphasis on a relentless improvement in the quality of graduates, so that eventually four graduates could do what five or even six workers could do today? Why not put public policy to work thinking about how to measure the degree of improvement? Why not get institutions and employers together to think harder and more consistently about what students do and do not need to know to be maximally efficient graduates, particularly in fields that are in high demand?
The idea of focusing on broad-based skills for innovation, or of focusing on quality rather than quantity, should not be considered radical. These should, in fact, be considered mainstream proposals. Indeed, in many countries they would be. But not Canada. And I have a theory as to why.
Back in the late Chretien period, the federal government was interested in skills and innovation, but had also agreed as part of a post-referendum re-juggling of federal responsibilities to hand labour market training over to the provinces in a series of MOUs. What ended up happening was that “skills” became exclusively tied to what was then called Human Resources Development Canada (HRDC, basically today’s ESDC) and tied up with notions of “employment security” – i.e. avoiding unemployment – while “innovation” became the territory of what is now Innovation, Science and Economic Development (ISED) and became tied up with notions of “cutting-edge industries”. In other words, “skills” became coded as addressing the needs of the bottom end of the labour market (and also provincial), while “innovation” was for the top end of the labour market (and also federal).
The result was two completely separate policy fields that not only act in silos but also see each other as opposites to some extent. At the same time, this created a situation where the (very small) independent policy market in Ottawa focused on innovation rather than skills because one was federal and the other was provincial. Consequently, we have a federal policy environment that seems willfully ignorant of the importance of skills in promoting innovative growth.
It doesn’t need to be this way.
