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Pearl Sullivan is dean of engineering at the University of Waterloo.

Whether we like it or not, computers are getting smarter. As more and more of us ask Alexa to add bagels to our shopping list or ask Siri to tell us what to wear today, artificial intelligence is permeating our world in increasingly surprising ways.

Although we aren’t anywhere close to the kind of dystopian futures imagined by Isaac Asimov or in Charlie Brooker’s Black Mirror, pressure is mounting on companies to capitalize on the potential of AI to help them change the way they do things.

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Whether it is tech giants such as Google and Apple, or retailers, taxi firms and factories, every business is eyeing the potential promised by AI to make them leaner, smarter and richer.

Stephen Hawking once said that “intelligence is the ability to adapt to change.” Before the machines can achieve true intelligence – and as humans move from the information age to the age of intelligence – we have to apply our own intelligence to assess whether and how AI should be used before we take the next steps.

The breakaway pace of digital progress, especially in AI, leaves some in the business community feeling left behind. A recent survey by the MIT Sloan Management Review and the BCG Group of 3,000 executives found that 85 per cent believed AI would provide a competitive advantage. But only 20 had “extensively” incorporated it into their businesses.

What this means is the relationships between universities and industry are going to become increasingly important. This partnership will need to be focused on growing a generation of “translational talent” – from a teamwork of AI developers and industry experts.

Universities, which are also mandated to advance knowledge, have a key role to play in ensuring the evolution of AI, its capabilities and the predicted impact on our future is clearly understood by their partners in business and industry.

This understanding will need to go well beyond the current applications offered by digital intelligence and algorithms, which are becoming ubiquitous and are reasonably easy to scale. We have still much to do to address the emerging challenges and opportunities presented by machine intelligence being embedded into cars, robots, smartphones and buildings, and even more is needed to advance human-centred intelligence that will enable AI to work with people in a way they can understand and feel comfortable with.

Technology such as AI is going to shift the global economy away from mass production toward mass personalization and customization. These are realities that are well understood by those who work with and research AI.

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They are realities that will underpin how companies and countries will fare in global competition moving forward.

To date, Canada is faring quite well in the race to develop and implement AI. The success of major industries, startups and the recent innovation supercluster commitments made by the government of Canada are evidence of that.

But to continue to compete, we will need to go much further. Barriers between those who produce AI knowledge and technology and those who require it need to be removed. Access to information on opportunities and risks should be easier, and could be accomplished, in part, by ensuring Canada’s educational model around AI includes teams of AI experts from universities working with domain experts from industry to educate students.

For its part, the University of Waterloo has established the Waterloo Artificial Intelligence Institute, which in addition to giving students access to such expertise, aspires to help its external partners solve their challenges through research in foundational AI. The institute also focuses on fundamental studies and theory as well as operational AI, which develops scalable, secure and transparent solutions for a wide range of applications.

The days of being able to operate in isolation are over. If individuals, companies and countries are to adapt to the economic disruption that is coming, we’re going to need to work together and ensure that what technology such as AI does and does not offer is clearly understood.

Companies will need to understand the implications of incorporating AI technology before they invest. Because if they don’t, the changes they experience may not be quite what they bargained for.

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