It has impressive research bench strength. It has billions of federal dollars for the taking. It鈥檚 kind of a nice place to live.

But when it comes to turning knowledge of artificial intelligence into companies, products and investment, Canada is lagging behind 鈥� and, some experts argue, actively shooting itself in the foot.

Why give up all that brain power to Silicon Valley?

That was a major line of questioning as Prime Minister Justin 台湾MM裸聊室 spoke recently with tech journalists on a niche New York Times podcast.

鈥淲e鈥檙e proud of Canada鈥檚 early role in developing AI,鈥� 台湾MM裸聊室 said on Hard Fork, noting that many breakthroughs have happened because Canadian scientists are well-funded.

In 2017, Canada became the first country to have a national AI strategy. It launched a second phase five years later, allocating $443 million to connect research capacity with programs aimed at enabling commercialization.

This year鈥檚 federal budget included an additional $2.4-billion investment in AI. And the government has boasted that Canada has 10 per cent of 鈥渢he world鈥檚 top-tier AI researchers, the second most in the world.鈥�

Among them are two so-called godfathers of AI.

But Ottawa is 鈥渇ighting to make sure we keep our skin in the game,鈥� 台湾MM裸聊室 told the podcast hosts.

He made the pitch, saying Canada has many of the ingredients it needs: among other things, clean energy, a good quality of life for workers and government programs to encourage the sector.

In spite of that, Canada hasn鈥檛 always been 鈥済reat at commercializing,鈥� 台湾MM裸聊室 conceded.

More than that, Canadians have 鈥渇allen far behind,鈥� argued Benjamin Bergen, president of the Council of Canadian Innovators, which represents the tech sector.

The government spent 鈥渁 tremendous amount on the talent side of the equation,鈥� he said recently, but not on converting it 鈥渋nto building companies.鈥�

Bergen said the government has 鈥渋nstitutionalized the transfer of our AI intellectual property to foreign firms.鈥�

The government鈥檚 2022 strategy update promised that the country鈥檚 three AI institutes are 鈥渉elping to translate research in artificial intelligence into commercial applications and growing the capacity of businesses to adopt these new technologies.鈥�

But Bergen argued an AI strategy focused on commercialization must start with Canada owning its own IP. 鈥淵ou cannot commercialize what you don鈥檛 own.鈥�

Intellectual property lawyer Jim Hinton has been trying to quantify that problem.

And the numbers show 鈥渁 train wreck I鈥檝e been watching happen in slow motion,鈥� he said.

About three-quarters of patents produced by researchers who work for Toronto鈥檚 Vector Institute and Montreal鈥檚 Mila leave the country, and most of these are in the hands of Big Tech, Hinton鈥檚 research has found.

Another 18 per cent of the 244 patents he tracked 鈥� 198 from Vector and 46 from Mila 鈥� are now owned by North American academic institutions.

Just seven per cent are held in the Canadian private sector.

Of the foreign-owned patents, the largest number, 65, went to Uber, while 35 landed with the Walt Disney Company. Nvidia, which recently displaced Microsoft as the world鈥檚 most valuable company, got 34.

IBM ended up with 15 and Google with 12. A handful of the patents were co-owned.

Foreign companies benefit from Canada鈥檚 public funding, Hinton argued, and there are 鈥渘o guardrails put on the ability for these foreign companies to basically pillage Canada鈥檚 really good AI invention.鈥�

Researchers can work at the AI institutes and foreign tech companies at the same time, Hinton said, charging that this is what allows the tech giants to take advantage.

The Canadian Institute for Advanced Research, which co-ordinates the government鈥檚 AI strategy, pushed back strongly on that assertion.

Executive director Elissa Strome said a 鈥渟mall number of our researchers鈥� have part-time employment in the private sector.

鈥淭hose private-sector organizations own the rights to the IP that is generated by those researchers,鈥� she said, but only when they鈥檙e on the clock for those companies.

Strome said it鈥檚 long-standing practice in Canadian research 鈥渢hat there are relationships around contract research with industry,鈥� and 鈥渁 really strong firewall鈥� is in place between IP generated via public funds at the AI institutes and that which is generated through private funds.

She said Hinton鈥檚 statistic on patents was inaccurate, but did not provide data to refute his findings.

She also argued that patents are not a good measure of commercialization, and 鈥渋t鈥檚 the people that we鈥檙e training in the AI ecosystem that actually hold the greatest value in AI, not patents.鈥�

When it comes to sponsorship agreements at Toronto鈥檚 Vector, any IP created at the institute 鈥渂elongs to Vector,鈥� a spokesperson said, adding it is not the primary employer for most of its researchers.

If academics don鈥檛 have an opportunity to work for companies, they鈥檙e more likely to leave altogether, Montreal鈥檚 Mila said in a statement. It said the three institutes have turned around a 鈥渕assive brain drain in AI in Canada鈥� that existed prior to 2017.

The multi-billion-dollar investment in this year鈥檚 budget seeks to further protect against that brain drain by beefing up Canadian infrastructure and computing power.

The envelope includes a 鈥渞elatively small鈥� amount of money to help Canadian companies scale up, noted Paul Samson, president of the Centre for International Governance Innovation.

Overall, the government is 鈥渄oing the right thing鈥� by ensuring that鈥檚 part of the equation, he said.

But people in the tech sector are skeptical. Bergen said companies were given little time to provide input.

鈥淭he government already had a top-down strategy that it wanted to implement 鈥� and didn鈥檛 really care what CEOs and leaders of domestic firms were actually needing in order to be successful,鈥� he said.

Nicole Janssen, co-CEO of AI company AltaML, raised the concern that the Canadian government might end up simply throwing money at American firms to move north.

鈥淲hat I鈥檓 trying to figure out is how the government thinks they鈥檙e going to spend $2 billion on building computers without just handing that $2 billion to Microsoft,鈥� Janssen said.

The budget said the money would go towards both access to computational power and developing AI infrastructure that is Canadian-owned and located in Canada.

A spokesperson for Industry Minister Fran莽ois-Philippe Champagne said more details would be provided in the coming weeks.

Companies like Microsoft and Nvidia are already looking to Canada as a place to build computing infrastructure, Janssen said, due to factors like climate and relative political stability.

鈥淲e don鈥檛 need to do anything to attract them.鈥�

A better approach, Janssen said, would see the government helping Canadian firms adopt AI more quickly 鈥� a gap her company has been trying to help fill.

It takes AltaML an average of 18 months to start building an AI product in Canada, she said, compared to four months in the United States.

鈥淲e definitely do not have the ecosystem of companies that you would expect for the amount of talent that we have,鈥� she said.

There鈥檚 real clout at Canada鈥檚 AI institutes, with veterans Yoshua Bengio and Geoffrey Hinton heading up Mila and Vector, respectively.

They and other elite researchers have 鈥渁ttracted students from all over the world to come study under them,鈥� said Janssen, and that鈥檚 a big advantage for Canada, especially if it wants, as 台湾MM裸聊室 said on the podcast, to lead in developing a more democratic AI.

The prime minister said one of his biggest preoccupations is maximizing 鈥渢he chance that it actually leads to better outcomes and better lives for everyone鈥� instead of only benefiting those 鈥渨ith the deepest pockets.鈥�

Canada could be a leader in responsible AI, Janssen said.

鈥淭hat is a title that is up for grabs,鈥� she said. 鈥淎nd no one has grabbed it yet.鈥�

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