Professor (Université Laval), President (CAIAC)
AI for business
The advances made in Artificial Intelligence (AI) over the past decade have transformed the world of business. New AI-powered consumer goods and services such as self-driving cars and smart homes are now available to the public. Both traditional business practices such as hiring processes and new business models such as Industry 4.0 all rely on AI as a cornerstone. And new career options, such as machine learning developer and data scientist, are available to AI specialists. A recent Accenture study shows that over 80% of Canadian businesses consider the adoption of AI as a necessity for growth and see failure to do so as a guarantee of bankruptcy; a number on par with international respondents.
Faced with this new reality, the Canadian government has acted resolutely to embrace AI and its applications to industry. Through new programs and increased funding, it has used its research organizations NSERC and MITACS to foster research collaborations between Canadian universities and industries. In addition, it appointed the research organisation CIFAR to lead its Pan-Canadian Artificial Intelligence Strategy, the world’s first national AI strategy, with one of its goals being to translate Canadian AI discoveries into real-world applications.
These actions have created a healthy AI ecosystem where universities and companies work together to create and market innovative ideas, and the benefits are being reaped by everyone in our country. The number of AI firms in Canada has increased exponentially over the past decade, and includes both major international players, such the new offices opened by Microsoft, Google and Facebook, as well as AI start-ups which are supported by unprecedented levels of funding. These new businesses create new career opportunities in AI and technology, and as a result the number of jobs in AI is increasing at twice the national average rate. University research labs also benefit from increased research funding and new research collaborations, which attract quality students (enrolment in computer science programs nationwide is nine times higher than the average post-secondary enrolment) and fosters a quality learning environment (three Canadian universities are among the top-25 for machine learning education worldwide). Nowhere is this symbiosis more visible than at the Canadian Conference on Artificial Intelligence, the annual meeting of university professors, graduate students, and industry researchers, where fundamental research breakthroughs and applied solutions to industrial problems are presented side by side.
AI and business for good
Of course, we should not talk about the rise of AI in business and industry without mentioning its darker consequence: the rise of algorithmic discrimination. Indeed, most AI systems learn from examples, and most examples come from human experiences or human decisions. This means that human biases and prejudices taint these examples and are learned by the AI systems. Those systems then naively repeat these prejudices and discriminate in their decisions based on them, negatively impacting both customers and companies.
But even in the face of this major complication, Canada has taken a leadership position. Canadian researchers wrote the Montreal Declaration for Responsible AI , which AI researchers here and internationally are encouraged to sign to commit to working on ethically-responsible AI projects. They also created the International Observatory on the Societal Impacts of AI with the mission of maximizing the positive impacts of AI and technology. Research labs and individual researchers across our nation are increasingly incorporating societal impacts and ethical responsibility in their research programs and integrating them into the curriculum of AI courses. After taking the leadership in AI for business, Canada is now taking the leadership in AI and business for the good of humanity.