Speer: Is Canadian politics shaped by “the revenge of places that don’t matter”?
Bridging the urban-rural divide in CanadaSaturday October 12, 2019
Together, automation and artificial intelligence (AI) have the potential to fundamentally reshape economics and social life. How will these trends affect politics and public policy? Will they expand or lessen the appeal of populism? Will they make it easier or more difficult for governments to shape public policy?
This report explores the potential for automation and AI to lead to widespread political and policy unrest and change in Canada. To examine this, we consider four related questions about automation and AI:
To understand citizens’ views on automation and AI and their related policy preferences, we surveyed 1,995 Canadians in May and June 2019. Our survey sample was drawn from multiple panels with quotas for age, gender and region, providing a representative sample of the population. Our goal is to understand how subjects’ objective exposure to automation and AI and their own beliefs about them—which may not align—relate to their preferences for various policy responses to the challenges of automation and AI.
We found that individuals have not aligned their expectations of the job loss effects of automation and AI with their own actual exposure. Individuals regularly underestimate their own exposure. When the time for reskilling comes, it will often be a shock, and a dislocating one at that. Policymakers will only be able to encourage people to take advantage of reskilling opportunities if those in the labour market understand their need for such reskilling. Accordingly, understanding how individuals can improve their knowledge of the particular skills they need for the future of their work is a pressing matter.
The political implications of our findings are as important as the technical policy implications:
The playing field is open for enterprising parties who wish to take up this policy challenge. Our political parties should do so with a depth and thoughtfulness equal to the challenge.