Canada and the Artificial Intelligence Revolution | AI | artificial intelligence

Leadership position in research is the advantage that needs to drive commercialization


Artificial intelligence is being called the “new electricity” as it revolutionizes business, employment, and society. Through fields such as machine learning, deep learning, and neural networks, AI is transforming everything from health care, agriculture, and construction to financial and professional services.

Research and advisory company Gartner predicted that almost every new software product would implement AI by 2020.

“AI is bigger than the internet in many ways,” said Karthik Ramakrishnan, Montreal-based Element AI’s vice-president of industry solutions, in an interview. “This is now the age of intelligence.”

AI can free up time for humans to undertake more creative endeavours by automating work that is tedious, repetitive, or dangerous.

It has not evolved to a state of general AI, where machines can think like humans—the nightmare scenario of HAL from “2001: A Space Odyssey.” Rather, AI is in its infancy, and experts believe that humans aren’t in danger of being replaced, nor are their interactions with each other in danger of vanishing.

AI is at the prediction stage, not at the judgment stage. Humans still need to set the objectives, provide feedback, and remain in charge.

Cameron Schuler, chief commercialization officer and vice-president of industry innovation at the Vector Institute in Toronto, said the best AI examples he’s seen are where humans are in the loop and are empowered.

“I look at it as a leverage point and the ability to actually change how we do things and make ourselves more valuable in terms of what we do,” Schuler said in an interview.

Canada is a world leader in AI research with three cities—Toronto, Montreal, and Edmonton—leading the charge of the national strategy. The three cities have thought leaders in University of Toronto professor Geoffrey Hinton; Yoshua Bengio, head of the Montreal Institute for Learning Algorithms; and Richard Sutton of the University of Alberta.

Canada’s AI ecosystem, with firms such as the Vector Institute and Element AI, seek to develop more talent to fill the enormous demand required to implement AI solutions in the corporate world and to keep Canada at the forefront of the revolution as global competition intensifies.

Setting the Stage

Schuler says AI was “a dead field for decades” due to a lack of professors to train the next generation. But in a perfect storm kind of way, with greater computing power, the internet and big data sets, Hinton’s research progress, and even people’s imaginations sparked by the movies, AI is back.

Machine learning algorithms can be built, and with limited data sets, the field of deep learning has taken on added prominence.

For example, machine learning doesn’t worry about rules. Instead, it learns patterns and figures out when there is an outlier event. To help a bank monitor and detect credit card fraud, for example, the software learns as people transact online what is unusual.

“We really should be approaching this as a problem first, technology second,” Schuler said.

It’s not just about how to implement AI, but also where to implement it within business processes. Companies need to rethink their workflows based on AI’s impact. People need to be prepared to perform higher-value-added tasks.

An example Ramakrishnan provided is that of streamlining the mortgage application process. AI can use optical character recognition and natural language processing to read pages and pages of documentation, check the validity of the customer’s inputs, assess the application in the context of the institution’s underwriting guidelines, and make a credit decision.

A process that can typically take nearly a month can be whittled down to a few days or even a few hours. The customer experience has been greatly improved and the efficient processing raises profitability. Scaling up such a process to accommodate greater volumes comes naturally.

Humans are left to make the judgment calls on exceptions—a far more interesting task than checking multiple pages of documentation.

AI could also lead to more quality human interaction in the case of doctors using tools to speed up diagnoses so that they can spend more time with their patients. Some say AI could even “re-humanize” us.

“It is going to impact a big part of your life, but in a positive manner,” said Schuler. “There probably isn’t an industry that won’t be touched by it. Yes, it is going to be quite revolutionary.”

Quest for Talent

An arms race is underway for AI talent globally. While Canada has spent over $500 million to get its national AI strategy off the ground, China is pledging more than $7 billion in AI funding, and cities like Shenzhen are providing more than $1 million for AI startups, according to analysis by Element AI citing the United States-China Economic and Security Review Commission.

“AI is seen not just as an enterprise-level competitive advantage but a country-level competitive advantage,” Ramakrishnan said.

The key for attracting and retaining talent is to develop the skills needed to deploy AI into the workplace. Ramakrishnan says it’s not entirely about the volume of talent but also the quality of it.

“It’s a bit of a land-grab right now from a talent standpoint,” Ramakrishnan said.

All figures in US$. (CB Insights)

Canada’s model of government, industry, and academia aims to create a feedback loop that provides funding and support, enterprise data, and top talent.

“All three have to play well and have to think in some ways ‘Canada first,’” said Ramakrishnan.

Canadian business needs to adopt and embrace AI and create more opportunities. China clearly realizes the potential of AI, as the country has doubled its patents since 2005 and has AI as a national priority.

Practitioners in the field consistently say, for example, that government procurement needs to support Canadian companies and startups.

As with tech in general, the challenge for Canada’s AI startups is to scale to become mature companies that use AI—to go from $10 million in revenue to $100 million. Here’s where access to talent and customers becomes critical. The capital is coming, as investment in Canadian AI companies in the second quarter of this year doubled that during the first quarter, according to CB Insights.

“Canadians’ conservative nature is not really focused on how do we invest in startups, because, well, we might lose money,” Schuler said. “It’s the nature of startup investing.”

A Unique Period

There is no question that the world is on the cusp of one of the biggest technological revolutions of our lifetime with AI, with Canada in a leadership role.

Humans have lived through change from the steam engine to the digital revolution. The next industrial revolution is getting started, but people can take comfort from knowing how economies and employment have adapted in the past. What’s different with AI is that ethical concerns about data privacy and transparency of usage still need to be addressed.

But for now, at AI’s current stage, the improvements are undeniable across several industries and awareness is growing of the employment impact and the demands for human talent going forward.

The economic opportunity for Canada is enormous; however, the country’s competitive advantages in AI are likely to continue feeling pressure from larger countries.

Follow Rahul on Twitter @RV_ETBiz

(Excerpt) Read more Here | 2018-08-01 21:12:10
Image credit: source


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