The AI Effect is a podcast series exploring Canada’s burgeoning artificial intelligence ecosystem. Accenture’s AI leader co-hosts with reporter Amber Mac to look at AI’s explosive growth and the change — challenges and rewards — it can bring for individuals, business and society.
In Episode 2, we talk with experts about how industry is adopting AI and the human implications that come with adoption.
Governments looking to move forward with AI often look at Estonia — a country that leapt from having no working phone system to one that provides nearly all its government services online.
It moved quickly by choosing practical digital innovations that leveraged AI to make a difference quickly. It prioritized those improvements that Estonians would notice right away when they needed to interact with the government.
It’s important for industry to make this leap forward, too — those that don’t do so risk getting left behind. We talked about this with Kathryn Hume, Vice President at integrate.ai, a company that helps clients use AI to solve their business problems.
Hume has two definitions for AI — a boring one and a fun one. We were of course intrigued by the fun definition. “I think of it as it’s whatever computers can’t do until they can. I like this because it bakes innovation into the definition itself.”
How then can businesses spot the opportunities where AI can have a meaningful and practical impact? Some organizations may expect the answer will magically arise from the data. But that's almost never the case. Businesses need to develop the acumen and skillsets on their teams to be able to recognize where the opportunities lie.
As everyone will tell you, AI is not without its challenges. At the top of Hume’s list is the data and the quality of the data. Organizations often have a lot of it, but that doesn't mean that it's available and actually useful for the algorithms.
Organizations, particularly large organizations, tend to operate based on linear processes and well-defined KPIs. AI is a probabilistic science; it uses statistical methods to make guesses, assign confidence rates and predict accuracy. The management culture required to operate in this environment is quite simply different.
Managing privacy is also key. All this will change the way people work in the near-term, says Hume, including C-level executives.
Our second episode also hears from leaders who are looking at the future of AI. Joelle Pineau at McGill University runs the Facebook AI research lab in Montreal. Her team of experts is focused on developing the mathematical models that will fuel the next generation of AI systems.
At the Montreal Institute for Learning Algorithms, CEO Valérie Pisano and her team of 220 researchers are focused on producing distinctive scientific findings in the world of AI while advocating for its ethical use. At the same time they are working with startups, SMEs and some of our larger Canadian companies, to help them bring AI solutions to life. One such organization is startup Imagia, that is finding new ways to detect cancerous cells.
We gain further insights from Cameron Schuler, Chief Commercialization Officer & VP, Industry Innovation at the Vector Institute for Artificial Intelligence in Toronto – a brand new role focused on looking at how the institute can be a catalyst for adoption within the ecosystem in Ontario. His view is that AI has the power to make industries like medicine, food production and even finance more “human-centric.” People worry about AI taking over, but adopting AI actually frees up time for humans to interact with each other.
And Elissa Strome, Executive Director for the Pan-Canadian AI Strategy at CIFAR, whose mandate is to advance our research expertise and our research leadership across the world, provides us with compelling reasons as to why we should care about all of this. AI has the potential for tremendous positive social and economic impact, but also positive environmental impact. So it's a technology that is really changing the way the world works.
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