Canada helped build the AI revolution. Now it’s time to lead it

Canada’s AI legacy is real and remarkable. Here’s what it asks of us going forward.

In a recent article on why it’s important for Canada to start acting like a civilization, I noted Canada’s connection to the development of AI:

“We have deep ties to the creation of modern AI, with Canadians like Richard Sutton, Geoffrey Hinton (British-Canadian), and Yoshua Bengio all playing key, foundational roles in what is now known as artificial intelligence.”

This is worth a closer look, because it’s something many people aren’t aware of, even as it says something important about the kind of country Canada is, and the kind of country we have the potential to build. Let’s start by looking at Bengio, Hinton, and Sutton:

Yoshua Bengio

Yoshua Bengio is a Canadian computer scientist born in Paris, raised in Montreal, and now among the most cited researchers in the entire history of science. As of November 2025, Bengio became the first AI researcher to surpass one million Google Scholar citations, and stands as the most-cited living scientist across all fields by total citations. His core contribution was to deep learning: the development of techniques that allowed artificial neural networks to learn layered, abstract representations of data, making it possible for machines to understand language, images, and complex patterns in ways that were previously unthinkable. He helped found Mila, the Montreal Institute for Learning Algorithms, which has become one of the largest academic centers for deep learning research in the world, drawing major research labs from Google, Microsoft, Facebook, and others to Montreal. He received the 2018 Turing Award alongside Geoffrey Hinton and Yann LeCun, often called the Nobel Prize of computing, for their collective role in building the deep learning revolution. Bengio has also been outspoken about AI safety and responsible development, chairing the International AI Safety Report and founding the nonprofit LawZero to build AI systems that are safe by design. He is a builder of the technology and also a moral voice within it, a combination that speaks directly to the kind of civilizational seriousness Canada should take pride in.

Geoffrey Hinton

Geoffrey Hinton is perhaps the most globally recognized name in the history of artificial intelligence. Born in Britain, he spent decades based at the University of Toronto, where he did much of the foundational work that now powers virtually every major AI system in the world. Known widely as the “Godfather of AI,” Hinton made key contributions in backpropagation, Boltzmann machines, and distributed representations, the building blocks that allowed neural networks to actually learn. In 2012, working out of the University of Toronto, he and two graduate students developed AlexNet, an eight-layer neural network that outperformed rival image-recognition programs by more than 40 percent, a watershed moment that proved deep learning could work at scale and triggered the modern AI revolution. The awards have followed accordingly: Hinton received the 2018 Turing Award alongside Yoshua Bengio and Yann LeCun for their work on deep learning, and in 2024 was awarded the Nobel Prize in Physics for his foundational role in enabling machine learning with artificial neural networks. He also co-founded and became chief scientific advisor of the Vector Institute in Toronto in 2017, helping cement Canada’s national AI infrastructure. That Canada was the home base for this work, the place that funded, hosted, and nurtured Hinton through his most consequential decades, is a fact worth sitting with.

Richard Sutton

Among AI researchers, Richard Sutton’s work is foundational in the most literal sense. Sutton is considered one of the founders of modern computational reinforcement learning, the branch of AI that teaches systems to make decisions by interacting with environments, receiving feedback, and learning from experience. The applications of this approach range from the AlphaGo program that defeated the world’s best Go players, to the reinforcement learning from human feedback (RLHF) techniques that shape how large language models like the ones powering today’s AI tools actually behave. Sutton became a Canadian citizen in 2015, and has long been based at the University of Alberta in Edmonton, where he founded the Reinforcement Learning and Artificial Intelligence Lab and co-authored what became the foundational textbook on reinforcement learning. In 2025, he and his longtime collaborator Andrew Barto received the Turing Award for developing the conceptual and algorithmic foundations of reinforcement learning, making the chief scientific advisors of all three of Canada’s national AI institutes Turing Award winners simultaneously. That fact alone tells you something remarkable about what this country has built.

The strength of Canadian pluralism

That all three chose Canada, and that all three have grappled seriously with the ethical weight of what they built, says something worth reflecting on. This country created conditions where foundational, patient, long-horizon research could happen, and it attracted people with the temperament to pursue it responsibly. When we talk about openness, to talent from around the world, to different perspectives and ways of being, it is often framed as a moral imperative. That is not wrong. But openness is also a competitive advantage. Canada built the kind of nation where people like Bengio, Hinton, and Sutton could make full use of their gifts. That welcoming spirit did not just do right by them; it did right by us.

The ethical dimension of this story is equally worth claiming with confidence. The fact that several of Canada’s leading AI figures have thought seriously and publicly about the responsibilities that come with this technology is a sign of maturity. Realizing AI’s potential for shared prosperity requires exactly the kind of long-term, fairness-minded thinking that has always been part of the Canadian character. That foundation is real, and it is ours. Now the task is to recognize it clearly, invest in it deliberately, and have the civilizational confidence to lead the defining technological transformation of our era.

Spencer Fernando

Photo by Céline Chamiot-Poncet:

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