While Silicon Valley often dominates the headlines, another city—quieter but increasingly potent—is shaping the future of artificial intelligence. Toronto, Canada’s largest city, has rapidly emerged as a global powerhouse for AI research and innovation. But what makes it so special? And what might the UK learn from Canada’s bold, ethics-driven model?
Over the past decade, Toronto has built a rare blend of academic prestige, public funding, private innovation, and ethical oversight. It’s home to the Vector Institute, founded in 2017 with backing from both the Ontario government and leading corporations like RBC, Shopify, and Thomson Reuters. It’s also the city where Geoffrey Hinton—often dubbed the “godfather of deep learning”—spent decades advancing neural networks long before they went mainstream.
Unlike the laissez-faire approach seen in the US, Canada’s federal and provincial governments have played an active role. The Pan-Canadian Artificial Intelligence Strategy, launched in 2017 and renewed in 2022 with £300 million in funding, prioritises not just innovation but governance and inclusivity.
Key pillars of the strategy include:
"Canada isn’t just building fast AI—it’s building fair AI."
Perhaps Toronto’s boldest experiment is its attempt to institutionalise ethical AI. The Vector Institute collaborates with universities and private partners to run real-time bias audits on large language models, while Toronto-based start-ups like SyntegrityAI and ProofCheck offer commercial “ethics-as-a-service” layers for enterprise software.
Schools across Ontario now include AI literacy and digital ethics in high school curriculums—something only recently adopted in parts of the UK.
The UK, while trailing behind in some areas of commercial AI application, remains a global leader in AI safety research, thanks to institutions like DeepMind and the Alan Turing Institute. However, British officials have increasingly turned their eyes across the Atlantic.
In 2024, the UK signed a joint AI research protocol with Canada aimed at harmonising standards on ethical AI. Areas of focus include algorithmic transparency, fairness in automated decision-making, and cross-border regulation for cloud-based AI services.
As a UK trade delegate recently noted, “Canada and the UK share more than a language—we share democratic values that must shape our AI future.”
Despite its progress, Toronto’s AI sector faces familiar headwinds: talent retention, venture capital bottlenecks, and a growing fear that regulation may stifle agility. In 2024, Meta quietly relocated a portion of its AI lab staff from Toronto back to the US, citing a “less permissive innovation climate.”
Additionally, smaller Canadian cities have struggled to keep up, creating concerns about an uneven AI landscape—with prosperity concentrated in Toronto, Montreal, and Vancouver.
What sets Toronto apart may not just be infrastructure—but people. Canada’s open immigration pathways for skilled AI workers, particularly via its Global Talent Stream programme, have drawn engineers and researchers from India, Nigeria, Iran, and Eastern Europe.
“Toronto is where the world’s AI brainpower collides,” said one recruiter. And unlike Silicon Valley, it’s doing so without pricing people out of the housing market—at least not yet.
For Britain, which faces similar ambitions but a smaller domestic market, Canada’s model offers insight. With clear policy, strong ethical frameworks, and talent-centred incentives, AI can be an inclusive growth engine.
Policymakers in Westminster have floated their own version of a UK-Canada AI Corridor, enabling cross-academic secondments, regulatory exchanges, and cloud-based model testing between the two countries.
As generative AI and autonomous decision-making continue to evolve, Toronto’s role will only grow. But it may not just lead in capability—it could lead in conscience. For the UK and others, watching closely may be more than strategy—it may be necessity.
The 2020s are shaping up to be the decade when nations chose not just how powerful their AI will be—but how human.
