Canada has been quietly investing in artificial intelligence research for the past 30 years, but according to Anthony Lacavera, academic investment may no longer be enough.
The wireless entrepreneur and startup investor believes that the efforts of the public sector to support research initiatives, such as the Canadian Artificial Intelligence Association (CAIAC) and many post-secondary academic programs, for several decades have created the foundation for Canada to become a global leader in AI.
As a result, two Canadian universities, the University of Alberta and the University of Toronto, have even gone on to be counted among the top 10 in the world for AI research, and several more have placed in the top 50.
However, the failure to bring this research to Canadian consumers in the form of products will leave Canada trailing behind other markets before we know it.
“From my perspective, the way to really get Canada into a leadership position in AI is to actually focus on commercialization,” Lacavera told MobileSyrup.
The goal of commercialization and integration is precisely what Next Canada’s NextAI program attempts to kickstart with its latest announcement.
NextAI launches new partnerships to stimulate the Canadian AI ecosystem
NextAI is the machine learning arm of Next Canada, a national, non-profit charity that looks to increase national prosperity through entrepreneurship and innovation.
NextAI will embark on several partnerships that will encourage Canadian AI startups to work towards introducing their products to Canadians.
In addition to partnerships with IBM Canada, Google and Nvidia, who’ve committed to supplying millions of dollars in equipment and resources, NextAI will launch several new funding propositions as well. To date, the funding for the program provided by all corporate partners totals $5.15 million CAD.
“We’re pairing researchers with business leaders. We want to demonstrate some early commercial success” – Lacavera
NextAI will also supply program participants with $200,000 in funding as well as access to mentorship, top-of-the-line technology and, most importantly, access to the world’s top AI academics from Harvard, MIT, NYU, the University of Guelph and the University of Toronto.
Connecting the academia that surrounds the AI community in Canada to the startups that want to bring it to life is a crucial aspect of making Canada a strong player in the space, says Lacavera.
“We’re pairing researchers with business leaders. We want to demonstrate some early commercial success,” said Lacavera, who also co-chairs Next Canada.
While Canadians are already seeing some early applications of AI across several sectors, machine learning has a long way to go before it becomes a well-understood and approved of practice among local residents.
Lacavera describes several sectors of the Canadian economy that would lend themselves well to AI initiatives, some of which are already working with data collection to enhance customer experiences.
He singles out financial services, healthcare, agriculture, education and automotive tech as places where the seeds of AI disruption have already been sewn.
Machine learning isn’t coming, it’s already here
Scotiabank executive vice president and co-head of information technology Michael Zerbs agrees with Lacavera’s selection and further corroborates the necessity of merging the academic and commercial sides of this field.
In addition, he argues that Canada is actually well situated to take on a leading role in AI in the eyes of the world over the next few years.
“Canada is actually in a unique place as we have a great opportunity to lead the development of AI. We’re also really excited about the opportunity AI has to transform the customer experience,” said Zerbs in an interview.
Fintech is one of Canada’s best examples of tech disruption as banks across the country begin to collaborate with startups and with academic institutions to better understand the increasingly digital-native Canadian population.
Scotiabank has previously launched initiatives to push AI development in collaboration with Queens, U of T’s Rotman School of Business, Western’s Ivy Business School and OCAD, among others.
“Canada is actually in a unique place as we have a great opportunity to lead the development of AI” – Zerbs
While it seems that banking is intently interested in the improvement of customer service, other sectors could benefit greatly from the efficiency and insights that come from machine learning.
In healthcare, for example, the ability to quickly and more accurately predict the onset of a serious illness through the use of AI could shave months off detection periods, therefore improving chances of patient survival. Furthermore, AI could one day be able to predict patient predispositions to illnesses years before they ever experience an outbreak.
In addition, Canada is on the cusp of ushering in the era of 5G connectivity, which will allow for the volume of on-platform decision making required by some machine learning programs. It seems that on most fronts, everything is falling into place.
Where do Canadians fit into this automated future?
Despite the massive potential that comes with such developments, talk of machine learning in the workplace has left Canadians worried about their own value as employees and has them wondering whether they could ever be replaced by an office version of Siri or Alexa.
While things are rapidly changing, Canadians need not worry. The jobs that exist today didn’t exist before the advent of the 20th century, and the coming years will usher in (and out) a plethora of roles as well.
Lacavera insists that companies have the opportunity to mitigate these changes now through several methods, such as proving training to employees. While job losses will likely take place in many sectors as more fields become automated, other jobs will inevitably open up elsewhere.
Zerbs adds to this by saying that while jobs will still be available, the nature of employment will change.
“Yes, some things will become automated, but it just creates new opportunities for insight. For judgment,” he concludes.
In this case, the value of judgment goes up.”
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