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Artificial intelligence, or AI, is poised to unleash another technological revolution and businesses need to embrace the coming change or risk being left in its wake, according to  co-written by Tiff Macklem, the dean of the University of Toronto’s Rotman School of Management. 

 

The op-ed, written with McKinsey & Co. partners Vincent Bérubé and John Kelleher, argues AI technologies will do for cognitive tasks what the steam engine did for physical ones – forever changing the world in the process. 

 

It comes as Rotman’s Creative Destruction Lab accelerator is set to host a sold-out conference Thursday on the business of AI called “” that will be attended by Prime Minister Justin Trudeau and a long list of AI researchers, entrepreneurs and investors.

 

“There is a growing consensus that AI will have a significant impact on industries, governments and societies around the world, which raises some questions about how best to manage the coming change,” Macklem and his co-writers say.

 

“The clear lesson from history, however, is that it is better to embrace the next platform technology than be a victim of its disruption.”

 

The authors offer two examples of how AI is being applied to established industries, including self-driving car algorithms capable of studying “millions of hours of human driving data” and natural language processing tools that predict “how to best respond to a customer by learning from thousands of previous conversations.” 

 

They go on to suggest several steps business executives can take to not only prepare their organizations for the AI revolution, but capitalize on it: 

Speakers at tomorrow’s annual Rotman event will no doubt emphasize the importance of embracing AI in the business realm. In addition to Macklem, the scheduled presenters with �鶹ֱ��app connections include: Sonia Sennik, the executive director of CDL; Ajay Agrawal, CDL’s founder and a Rotman professor of entrepreneurship, Russ Salakhutdinov, a �鶹ֱ��app alumnus and associate professor at Carnegie Mellon University who heads up AI research at Apple; and Elizabeth Caley, a �鶹ֱ��app alumna who is the chief of staff at Meta, an AI-powered tool that searches scientific papers and was purchased by the Chan Zuckerberg Initiative earlier this year.  

 

Of course, the application of machine learning and other AI technologies to industries ranging from finance to transportation won’t be seamless. 

 

A, for example, cited efforts by Anna Goldenberg, a scientist in the genetics and genome biology program at SickKids Research Institute and an assistant professor in �鶹ֱ��app’s department of computer science, to use machine learning algorithms to “identify hitherto obscure subcategories of adult-onset brain cancer, estimate the survival rates of breast-cancer patients, and reduce unnecessary thyroid surgeries.”

 

The catch? The article notes it can be difficult to attain U.S. Food and Drug Administration approvals for AI-powered systems because the current regulatory framework doesn’t permit drugs and health-care equipment to be altered once they’ve been approved for safety reasons. Machine learning, by contrast, is a technology that shifts and changes over time as algorithms are fed new data and results become more accurate. 

 

The article also quotes Liam Kaufman, a �鶹ֱ��app alumnus and the CEO of WinterLight Labs, which analyzes patients’ speech patterns with AI algorithms that can detect cognitive impairment. Kaufman tells the magazine he’s unsure whether his technology will be ready for FDA approval “in part because it is still unclear whether such approval would require that he freeze his product in a defined state.”