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It's rare for Canadians to come out and assert global leadership in anything (barring hockey and winter coats), but here we are, on the brink of adding artificial intelligence (AI) to the list.

This is no small measure. It requires us to move away from the understated modesty that often defines our national character and demands that we take action to be able to declare our place on the world stage.

Thankfully, we have the goods to declare. Seminal breakthroughs such as deep learning and reinforcement learning, which have resulted in unprecedented technological transformation and are currently fuelling the AI engine, were brought to life by Canadian universities. Machines trained on deep-learning algorithms can now automatically recognize objects, translate speech in real time and enable the contextual understanding of data, while reinforcement learning has provided the intelligence that allows computers to beat human world champions in complex and sophisticated games such as Go.

These pioneering achievements can all be traced to labs in Edmonton, Montreal and Toronto.

But in order for our made-in-Canada story to emerge, we need all participants in the AI ecosystem to align behind the same goal. Universities, institutions, startups and enterprises need to work together for the greater good.

The good news is some wheels have finally started to turn. Over the past few months, industry and government have pledged more than $500-million toward AI, a commitment that has led to the rise of powerful institutions such as the Montreal Institute for Learning Algorithms, the Vector Institute and the Alberta Machine Intelligence Institute. These structures are well positioned to keep churning out cutting-edge research, train the next generation of AI leaders, and advance the innovation and technology transfer of AI.

However, there's still a major gap to close. The majority of Canadian enterprises are not yet at the forefront of AI innovation, despite the fact that many of the world's leading research scientists are sitting on their doorstep. A recent study by RBC Economics shows that only 13 out of the country's 60 largest companies are currently making material investments in AI.

We're facing a critical moment in determining whether history will remember Canada as a leader or bit player at the advent of one of the biggest technological leaps in human history. There's an urgency to act now and act wisely.

And while we've made many of the right moves, we need to do more.

A good place to start is by preserving our own intellectual assets and creating an environment that entices our academics to remain local. Academics help facilitate this shift by training students and company employees on the latest advances, while young entrepreneurs should consider scaling their companies on Canadian soil where they can benefit most from our rich brain trust.

Traditionally, Canadian businesses have lagged on productivity and, as a result, the country has been slower to attract investment and create jobs than other economies. In the AI space, Google has been retraining 5,000 of its engineers in machine learning and, as a result, was able to push to market deep-learning tech at an unprecedented speed.

Our three AI Institutes are set up to offer Canadian businesses similar training programs and there's good reason for them to use these resources: Canadian enterprises that consider investing in state-of-the-art machine-learning and data infrastructure can enjoy results such as increased efficiency in manufacturing, better management of underwriting risk, minimization of fraud and reduction of health-care costs.

We also do better by giving early opportunities to researchers in Canadian companies and encouraging them to become homegrown winners. Companies will find a federal government open to ideas and do well to take advantage of Ottawa's recent announcement for supercluster funding through participation and support of the AI cluster. At the same time, Canadian enterprises can help incubate and scale up small businesses or spinoffs while fostering meaningful partnerships with Canadian universities and research centres.

This is particularly important for a field whose lifeline depends on access to massive data sets owned by the few. Scientists benefit from government and industry collaborations that enable privacy-protective sharing of data and information. This level of access can spearhead novel AI solutions in areas such as machine automation, security and medical diagnostics. For instance, Canadian provincial health-care ministries have invested in digitizing patient records and by covering 100 per cent of the population, this information serves as a unique asset to present researchers with a major competitive advantage.

Money, while crucial to this development, is not enough. The government will help tilt the AI playing field in Canada's favour by ensuring our policies keep Canadian firms competitive. We hold a strong advantage already with our open borders and the government's receptiveness to change. But progress requires action and there are tangible steps left to take. Among the most urgent are ensuring the market is well supplied by streamlining immigration, ensuring higher education and industrial research-funding programs are well capitalized and targeted, modifying tax policies to encourage entrepreneurship and streamlining research and development tax credits to support AI investments.

The government can also consider a Canadian fund or additional support mechanisms to encourage the patenting and commercialization of intellectual property in Canada.

All parties are responsible for creating an accessible AI ecosystem that generates value and wealth for our entrepreneurs, investors, businesses and academics. From that baseline, it becomes a self-sustaining system in which good things start circulating back into the environment and allow the stakes to rise.

Let's talk about seeing this vision through and embrace the daring mind-shift of taking on a goal to be a world leader. We need to move fast, with long strides and every party focused on the same prize. It's ours for the taking.

Foteini Agrafioti is CSO and Head RBC Research Institute, Yoshua Bengio is professor at the University of Montreal and head of the Montreal Institute for Learning Algorithms and Tomi Poutanen is co-CEO of Layer 6 AI and a founder of the Vector Institute.

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