Innovation presents widely-acknowledged benefits to society, including economic growth and social and cultural well-being. However, the benefits of innovation are often not distributed equally throughout society. How can government policies encourage innovation economies that are more inclusive, and what are the barriers we face in doing so?
Following on a public webinar hosted by the Munk School of Global Affairs & Public Policy at the University of Toronto with the support of CIFAR, the panelists, including members of CIFAR’s Innovation, Equity, & The Future of Prosperity research program, participated in a virtual briefing on December 18, 2020 with policymakers in the federal government of Canada. Through an interactive panel discussion, this briefing was an opportunity for researchers, civil society leaders and government policymakers to identify and share mutual interests and priorities in equality, innovation and distributive growth. This report highlights key messages from the conversation at the webinar and the briefing.
Key Insights and Priorities
“Innovation” refers to the application of knowledge to develop new or improved products, services, or organization of work, with a view to generating economic and social value, such as higher productivity or better environmental sustainability. “Inclusiveness” encompasses three criteria: participation (by all people as workers, entrepreneurs, students, etc.), distribution (of benefits and access more fairly), and empowerment (ensuring everyone has the opportunity to contribute to decision-making about innovation in firms and society more broadly).
There isn’t necessarily a tradeoff between innovation and inclusiveness — in fact, a more inclusive innovation system would not only be more fair, but could help society and the economy grow faster by allowing more people to contribute. The goal of a “distribution-sensitive innovation policy” is to grow the value of innovation without increasing inequality, and perhaps even decrease it.
Canada is neither as innovative as it can be, nor as inclusive as it aspires to be.
Canada punches above its weight in terms of inventions, and has opportunities to develop production chains and networks that can turn these inventions into further innovation within the country and capture the benefits of invention. There is a need to develop a true innovation policy that is longer term than a budgetary cycle and institutionalized within the civil service and public agencies.
The “thickness” of the conversation about inclusiveness must also be increased, beyond simply discussing participation, but also the trickier dimensions of distribution and empowerment, in order to lead to more substantive changes. For example, while many racialized groups in Canada have in the innovation sector (and tend to have higher educational attainment than their peers), they receive lower pay, and feel less empowered to bring their innovative ideas to the table and know that their contributions will be valued.
The trajectory of innovation is not deterministic but can be shaped by policies and human intervention. While many examples of current digital innovation increase inequality by disempowering workers (e.g., sensors that stop the stamping press in an automobile manufacturing line whenever issues are detected and require a supervisor to resolve every issue), they can instead be used to empower workers (e.g., where workers are upskilled and trained to deal with some of the sensor-flagged issues on their own).
For the past quarter century, Silicon Valley and Israel have often been touted as models for innovation. However, these are also two of the most unequal societies. A venture capital-based model of startups tends to benefit engineers (mostly from well-resourced research universities), investors and lawyers, but few real jobs are created; while value seems to be created for some people, it is often just a reshuffling of existing value. There is a need to look for other models.
For example, in Europe (particularly the Nordic countries), discussions about national R&D and innovation strategies more commonly involve unions in the conversation, which could lead to innovation that better empowers workers while also helping to convince them to support innovation because they know it will not lead to job loss. Another model could be Taiwan, which, during the COVID-19 pandemic, has been able to quickly shift its manufacturing output to focus on personal protective equipment and ensure its equitable distribution. A caveat of these models is that these are more homogeneous societies than Canada and thus may not fully translate to the Canadian context.
Within Canada, lessons can be learned from some regional/local examples including Newfoundland (where some of the profit from fossil fuel extraction is channelled to education and R&D to help reskill the population), the Hamilton, ON area (with a homegrown cluster of life sciences companies focused on health), Western development programs (with consideration for rural and Indigenous populations and the challenges to accessing resources due to geography, and providing “wraparound” support services including networking and mentoring), and some trades programs for Indigenous communities (which provide flexibility or additional support based on factors such as distance of travel or time needed for cultural commitments).
To support inclusive innovation policies, there needs to be better data and metrics, through more systematic collection and bringing together both the innovation-focused and the inclusion/equity-focused policy communities, so that the conversation is not just based on anecdotes. Such data would provide the baseline for measuring the impact of policies.
While some data are available for women, they are much harder to come by for many racialized groups or gender-diverse individuals. Other dimensions that need to be included are region/geography, disability, and skill level.
The “right” outcomes for a policy goal also need to be measured, e.g., number of jobs created rather than how “innovative” a company is, or the impact on non-market work (the burden of which often falls on groups currently underrepresented in the labour force). A distribution-sensitive innovation policy will require thinking about how a policy affects economic distribution, whether this effect is desirable, and if not, how it can be prevented or mitigated.
Dan Breznitz, Co-director, Innovation Policy Lab, and Professor, University of Toronto / Co-director, Innovation, Equity & The Future Of Prosperity program, CIFAR
Susan Helper, Professor, Case Western Reserve University / Co-director, Innovation, Equity & The Future Of Prosperity program, CIFAR
Daniel Munro, Senior Fellow, Innovation Policy Lab, University of Toronto / Research Advisor, Brookfield Institute for Innovation + Entrepreneurship
Anjum Sultana, National Director of Public Policy & Strategic Communications, YWCA Canada