• Jamie Read

Canadian AI at risk of becoming the next BlackBerry

Updated: Dec 6, 2018

Let's face it, Canadian companies have been inconsistent as it pertains to tech innovation and their adaptation to a fast-changing world. If they aren't careful Canada's world-leading AI companies could get caught naval gazing and one day find they are the laggards.

As Canada leads the global push for Artificial Intelligence, particularly deep learning applications, here are five risks and rewards that should be considered in order to avoid the fates befallen the Avro Arrow, Nortel and BlackBerry.

1. Adoption - According to a recent article published by the Financial Post, Canada's AI expertise is under threat as the technology advances quickly and companies around the world start to apply it more broadly. The article suggests that Canadian companies aren't adopting the technology quickly enough, citing an Accenture 10-country survey which places Canada 9th on the list just ahead of Brazil.

If Canadian AI is going to be successful in the long-term, we need to make sure Canadian companies are using it first. The barrier to entry doesn't need to be high but because Canada's expertise is grounded in academia, the terminology can sometimes make the technology seem inaccessible. As such, governments, agencies, even smaller startups looking to make an impact should invest in outreach programs and incentives to educate and entice companies across industries to test and adopt artificial intelligence.

2. Application - When Canadians hear about Chinese applications of AI, they tend to think about the 'Big Brother' or robot military scenarios played out in Western articles. And while it's true that China has less debate about the ethics of AI applications, ultimately their government is driving AI forward and the applications are countless. Baidu, for example, leads AI patent applications in China with 2,368 filings. Canada, on the other hand, isn't adopting the technology as fast (as mentioned above) and so it isn't diversifying the technology's applications either.

It's true that Canada is a pioneer in deep learning and the main reason why we are world leaders in the field is because institutions such as the Canadian Institute for Advanced Research are doing well to execute the federal government’s $125-million Pan-Canadian artificial intelligence strategy. This funding supports three centres of excellence — the Alberta Machine Intelligence Institute in Edmonton, Mila in Montreal and the Vector Institute in Toronto. But if Canada wants to be known for more than just world-leading AI thinking, we need to move from theory to practice.

So where should we start? Well according to Google Trends, it's no surprise that the top subjects associated with AI revolve around sex. The porn industry has consistently been prescient in its application of technologies — VHS, peer-to-peer, VR, live streaming and now AI. I'm not suggesting this is where Canadian AI should put all its efforts, but leaders lead, often in unexpected ways. Canada's AI industry would do well to think creatively in order to make some noise and raise its profile.

3. Attitude - As I mentioned, leaders lead and if Canada truly sees itself as a global leader in AI, we have to be bold. Brand Canada has never been stronger around the world. According to Edelman's Trust Barometer, we are the most trusted country. So when it comes to who companies around the world will trust to apply machine learning to their sensitive data, Canada has a big advantage.

But we are humble and polite and conservative. We have a big English speaking market to our South, so why bother looking anywhere else? It's a new field, so why don't we wait and see which way the wind is blowing? Questions like these are what have hurt Canadian tech companies before. Fortune favours the bold!

3. Talent - Talent is often cited as one of the major challenges in the AI industry. In Canada, we're blessed with world-leading courses and universities that build on our reputation as pioneers and leading thinkers. However, education is also a great chance for Canadian AI to market themselves, while building a talent pool around the globe. Google and Nvidia are two AI heavyweights who are investing in education programs for both the general public and for those looking to tap into future-forward careers.

If Canada's AI companies want to compete on a global stage, they should consider how webinars, free courses and university/government tie-ups can be created for people around the world. This is the very fundamentals of thought leadership, and it is imperative for the success of Canadian AI.

5. Location - I love Canada. It's my birthplace and where I keep my stuff but it is ultimately a small country. Canadian companies who remain local will be limiting their potential (and profits). With global trade in a state of flux, particularly with our American neighbours, and Canada's brand recognition at it's highest levels around the world, Canada's AI companies have an unprecedented opportunity to expand into new markets and support the adoption of AI in fast-growing economies that aren't bogged down by legacy infrastructure or systems.

For those that are interested, Vector Institute and MaRS are hosting An Introduction to Artificial Intelligence in Toronto on December 17th. Also, the Canada-ASEAN Business Council (of which I am a part) will be hosting an event in January in partnership with Fasken called 'Canadian AI and the ASEAN Market Opportunity', which will provide insights on how AI companies can grow their business in Asia. If you're interested in participating or attending, please reach out.

What do you think about our first Brite5 post? Please feel free to add any other challenges or opportunities you believe are affecting Canadian AI.

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