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Blair Attard-Frost is a PhD candidate studying the governance of artificial intelligence at the University of Toronto’s Faculty of Information.

In 2017, the Canadian Institute for Advanced Research (CIFAR for short) launched its Pan-Canadian AI Strategy. Driven by $125-million in federal funding for nationwide artificial intelligence (AI) research and training programs, CIFAR’s initiative made Canada the first country in the world to implement a national AI strategy.

By 2018, Canada was rapidly becoming a hub for some of the world’s leading AI researchers. Burgeoning AI startup ecosystems in Montreal and Toronto made Canada an incubator not just for AI innovation, but for guidelines that could be used to steer that innovation for the public good, as outlined in the Montreal Declaration and the Toronto Declaration.

For a little while, Canada’s message was clear: AI represents a once-in-a-generation opportunity to create broad-based economic prosperity for Canadians by harnessing innovative new technology, and the country was prepared to seize that opportunity. In 2022, however, it’s become clear that we are failing to follow through on our stated goals. All we have right now is a messy constellation of disconnected programs and initiatives.

To list just a few of these programs: In 2019 the Treasury Board of Canada implemented its Directive on Automated Decision-Making to manage the federal government’s procurement of AI products and services. In the same year, Innovation, Science and Economic Development Canada (ISED) assembled AI experts from industry and academia to form an Advisory Council on Artificial Intelligence. ISED also runs the $1.8-billion Innovation Superclusters program, which leverages innovative technologies like AI to spur economic development in specific sectors and industries across the country. Ontario, Quebec and Alberta all have their own provincial plans for fostering AI-based economic development, and Ontario also has its own framework for ethical AI use, even though the federal government and other provinces do not. Even municipalities, including London, Ont., have launched their own AI initiatives. Trying to identify Canada’s overarching strategy for AI is like playing whack-a-mole with a long list of initiatives across the country: just when you think you’ve found every region’s AI guidelines, three more examples pop up.

The feds were forward-thinking, to a point. They knew we would need a comprehensive, nationally integrated approach to this problem, and commissioned an AI strategy from CIFAR in 2017. Unfortunately, CIFAR’s own reporting has since revealed that while Canada’s AI strategy has remained narrowly focused on AI research and development, the strategies of other wealthy nations have evolved more comprehensively to include work force development, industrialization, data infrastructure, inclusivity and social well-being.

You don’t need an AI system to detect a pattern among these data points: Though it was once a promising global leader in AI strategy, Canada has now fallen behind other countries and faces a labyrinthian mess of disjointed policies and programs.

China and Japan have specific, long-term visions for the role of AI in their societies, while the United States and European Union have well-defined mechanisms for co-ordinating AI-related strategic planning, policy development, research and investment between departments and governments. Canada does not.

We also lack a cohesive plan for retaining AI talent, capital and intellectual property to guarantee that our investments in AI will actually benefit the economy in the long term, and we lack a meaningful commitment to engage the public in decisions related to AI strategy. A recent Ipsos poll revealed that Canadians are among the least likely to believe that AI will improve their quality of life, ranking 27th out of 28 countries surveyed. The skepticism that the Canadian public shows toward AI is an indictment of the federal government’s inability to deliver on its promise of broad-based economic prosperity.

Fortunately, there are already some institutions in place that can help us solve these problems.

CIFAR is in the business of science and technology research, not the business of geostrategic planning. An interdepartmental and intergovernmental Strategic Council for Canadian AI needs to be formed. CIFAR should then leverage its own strengths to act as the primary knowledge broker for this council, which would receive synthesized reporting on the overall state of AI in Canada.

CIFAR should regularly collect and provide this strategic council with detailed data on the sentiments and needs of the Canadian public, providing evidence-based policy recommendations, administrative best practices, and lessons learned from other jurisdictions for a co-ordinated, all-of-government approach to AI strategy.

The knowledge collected by CIFAR, as well as the activities undertaken by a strategic council, should be shared openly and the public continuously involved in the council’s decision-making processes.

Canadian leadership in AI will require a clear, long-term vision, well-coordinated and integrated planning, and meaningful public involvement. Right now, none of those attributes are on display in Canada’s AI strategy.

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