This op-ed was originally published on Apolitical. It is written by Sarah Doyle, Director of Policy and Research at the Brookfield Institute for Innovation and Entrepreneurship and Hasan Bakhshi, Director of the Creative Industries Policy and Evidence Center (PEC); and the Executive Director of Creative Economy and Data Analytics at Nesta.
In fact, many forces, from AI to climate change and the aging of the population, are reshaping the jobs that will be available down the road, but in ways that are difficult for us to predict. Governments everywhere acknowledge the need to invest in new skills for workers in vulnerable jobs, but which skills do they need?
While it’s clear that no one has the tea leaves or crystal balls required to paint an accurate picture of the future, forecasting can be a helpful tool for considering the range of possibilities, thereby enabling more robust decisions on reskilling to be made.
Many forecasts, however, assume that historic trends will continue.
This fails to take into account the possible impacts of extraordinary disruptions, resulting from, say, breakthrough technologies, changes in the natural environment, or shifts in policy.
The Brookfield Institute has teamed up with Nesta — a leading innovation foundation based in the UK — to develop long-term skills forecasts for Canada (forthcoming in early 2020), combining predictive modeling with expert insights, which take into account how a wide range of changing trends might interact to shape the future of work. In doing so, we aim to identify the skills that will better equip us to navigate uncertainty. Our goal is to help employees, employers, educators and governments in Canada make more future-proof skills decisions.
Who knows what tomorrow holds?
Our approach starts from three insights.
First, there are clear trends in the workforce composition of developed economies, such as a rising share of management occupations and declining share of production jobs in the US, but such changes are gradual. This suggests that looking back at the history of employment is a good starting point for making predictions about the future.
Second, the workforce in all countries is exposed to new sources of disruption, such as the effects of climate change and the AI revolution, meaning that simple extrapolation of the past paints a distorted picture of the future.
And lastly, occupations are complex. Even seemingly straightforward jobs, on reflection, require a subtle configuration of knowledge, skills and attitudes, suggesting that the models we use to generate quantitative forecasts must look beyond simple occupational categories.