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Consider this: Artificial Intelligence is much more advanced than people realize.

Or, maybe not.

Professor  Ajay Agrawal posed both theories in his welcome to a sold-out conference at the ������Ƶ on Dec. 15. More than 20 people spoke at the event, entitled . And there were divergent opinions at the conference about just how smart machines are or will be. 

Agrawal, founder of the Creative Destruction Lab at U of T’s Rotman School of Management, said “nobody is certain whether we are on the brink of an AI revolution or simply enjoying a brief reprieve from the AI winter. However, almost everyone is certain that significant economic turbulence is coming given the falling cost of processing power, storage and sensors, coupled with the rising collection of data from mobile devices, wearables and other so-called Internet-of-Things devices, all occurring as algorithm performance marches steadily forward.”

Governor General David Johnston opened the session by telling the group of scientists, entrepreneurs, leaders in industry and government and students that “we truly do need creative minds and inspired groups of people to move us ahead in these transformative times. There are few spheres in which the transformation has greater potential impact than in the realm of machine learning [ML] and artificial intelligence.”

Johnston (pictured below, with U of T President Meric Gertler, in a photo by Eugene Grichko) quoted Marshall McLuhan, saying “to bring order into this jangled sphere, man must find his centre” and added “that is what you are here to do, with regard to machine intelligence.” He also noted that “Canadians have been at the forefront of some exciting new developments of machine learning.”

Agrawal told the audience they would hear from entrepreneurs using machine learning in some very specific markets but “I urge you today not to fall into the trap of focusing on the small, narrow markets, and lose sight of the potential of a much bigger effect on the overall economy-wide possibilities of machine intelligence.”

Advances in machine learning have led to improvements in medicine and lifestyle but still do not amount to a transformational impact on the economy, Agrawal said.  

“I suspect the reason the driver-less car has become so iconic is because it offers us a glimpse at something much bigger,” he said.   

Entrepreneur Shivon Zilis, co-host of the conference, gave one example of the new economy using ML, in an area that many people are unaware of – agriculture. Zilis (pictured below in a photo by Eugene Grichko) showed a picture of a tractor equipped with cameras that “made decisions in real time” about whether lettuce plants were healthy or needed pesticides.

Just before the lunch break, Toronto Mayor John Tory, Johnston and U of T President Meric Gertler helped hand out awards from the Creative Destruction Lab to the University of Waterloo’s engineering and co-op program, entrepreneur Haig Farris and the Canadian Institute for Advanced Research (CIFAR).  

Tory said this country needs institutions such as CIFAR and the Creative Destruction Lab “given our tendency not to recognize our resident brainpower.” He said it is part of his job to make sure such people don’t have to leave town to become innovators and entrepreneurs. “In fact, they shouldn’t leave town. They should stay here and encourage others to join them here.”

One of the most distinguished speakers during the afternoon session was Professor ������Ƶ, who once told Wired Magazine that researchers in artificial intelligence “are no longer the lunatic fringe; we are the lunatic core.”

Hinton (pictured below in a photo by Johnny Guatto) and his lab at U of T made major breakthroughs in deep-learning methods and applied those to speech recognition in 2009 and to object recognition in 2012. He has divided his time between U of T and Google since 2013.

The professor gave an academic lecture on artificial neuron networks that he said would have “big implications for document processing” noting that scientists are building towards machines having “sequence of thoughts, which is just rationale reasoning.”

But “we are not there yet,” he said.

Asked to look into the future for machine learning, panellists spoke of a world where “kids will not be driving cars that we think of as cars today,” a world where “we can deal with global warming,” and where, eventually, machine learning “will permeate every aspect of life.”

Nick Bostrom of Oxford University said if AI succeeds there will be a “fundamental change in the human condition,” akin to the “rise of homo sapiens.” 

Asked about the future challenges and uses of deep learning, Hinton said it should be used to “Uberize the real estate market, to get rid of the parasites that charge five per cent” to help find a house.   

At the late afternoon session some speakers raised ethical and privacy issues around AI, including the “technological displacement” of workers no longer needed in many industries. One panellist noted that there are now two million industrial robots in the world, with 200,000 sold every year.

Stanford University’s Jerry Kaplan wrote in the handout given to participants at the conference that “what Karl Marx couldn’t foresee is that synthetic intellect can also substitute capital for your mind. So the conflict he characterizes between poorly paid workers and highly compensated managers – people against people – cuts the wrong way. The real problem is that the wealthy will need few, if any, people to work for them at all.”

Kaplan told the audience: “Marx was right.”

Professor Steve Mann (pictured below in a photo by Eugene Grichko) is chief scientist at the Creative Destruction Lab, and considered the “father of the wearable computer”. Mann told audience members the world should not think about artificial intelligence. It should consider HI – Humanistic Intelligence.

Speaking just after John Markoff of The New York Times, Mann read a passage from Markoff’s book, Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots. 

“As computer systems are woven more deeply into the fabric of everyday life, the tension between augmentation and artificial intelligence has become increasing salient. This is about us, as humans, and the kind of world we will create. It is not about the machines.”