Pepper the robot appears on stage with a Softbank executive at CES in Las Vegas on Jan. 7, 2016 Credit:James Niccolai
There was once a time when no one thought computers could master chess; then, in 1997, IBM's Deep Blue beat chess champion Garry Kasparov. The bar then moved to the ancient Chinese game of Go -- until Europe's reigning human champion fell to Google's AlphaGo system late last year.
One by one, artificial intelligence has overcome the obstacles set before it. Is this all part of an inevitable trend leading to humanity's obsolescence -- or, at least, unemployment?
Just last month, a World Economic Forum report warned that AI, robots and other tech advances will take more than five million jobs from humans over the next five years.
Here's an example: There are currently more than 230,000 taxi drivers in the U.S., according to the Bureau of Labor Statistics -- not counting Uber or other alternatives.
"Once driverless cars are mainstream, all those jobs are going to go away -- those people are going to have to find something else to do to support their families," Upadhyay pointed out. "That's disruptive."
It doesn't mean "the machines" are on a quest to destroy our lives, however.
"I don't buy into the idea that machines have purpose and a value system and are somehow out to destroy the world," said Upadhyay, who was formerly a data scientist at Cornell University. "I think we'll coexist."
In fact, AI can in many cases free humans from tasks they're not particularly well-suited for in the first place and allow them to concentrate on what they do best, he suggested.
Marketing -- the focus of Lattice Engines -- is one example.
"When we first introduced our predictive-intelligence product in 2011, it could probably outperform about half the people in a sales organization," Upadhyay said.
Specifically, the system was better than roughly half at predicting when a prospect would make a purchase.
Five years later, the technology has "seen" so many more examples of who buys and who doesn't that it can now outperform roughly 90 percent of salespeople at that prediction, he said.
"In a way, it's looking through data from 20 million U.S. businesses -- that's something no sales rep can ever put in their head," Upadhyay said.
The effect, though, isn't that companies get rid of all their salespeople and replace them with predictive-marketing software. Rather, it's changing the human focus from predicting who will buy to closing the deal, he pointed out.
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