Why Watson Matters: The Impact of Mainstream Machine Intelligence

By TechZone360 Special Guest
Marius Moscovici, Founder & CEO, Metric Insights
September 26, 2014

“The answer to the ultimate question of life, the universe, and everything is...42.” So said Deep Thought, the fictional supercomputer in “Hitchhiker’s Guide to the Galaxy.”

Back to real life in 2014: enter IBM’s Watson. Everyone from Google to the government is investing in the cognitive technology that will redefine what it means to be human. While we’re a far cry from the advent of robot dominion, machine intelligence is already driving a Darwinistic effect in business—and we should all be paying attention.

Roughly the size and shape of three stacked pizza boxes, Watson makes decisions in seconds versus minutes and can do anything from advising call center operators to suggesting cancer treatments. If IBM has its way, the supercomputer will eventually find its way to the desktop of the average corporate employee.

It won’t be the only intelligent machine assistant to permeate our daily lives.

Machine Intelligence Emerges into the Mainstream

After living in a sleeper cell for years, cognitive technology is finally positioned to change the way we live. It took until now to make machine intelligence, which has been around since the 1940s, widely applicable.

Big data and cheap computing power had made it possible to affordably scale machine algorithms on massive data sets. As a result, daily-use innovations like self-driving cars, smart thermostats and surgical robots are finally emerging into the mass market.

Well-learned machines could eventually transform life as we know it. The tech sector and the government are investing in precisely that outcome. The AI company Vicarious, backed by Elon Musk, Mark Zuckerberg, Peter Thiel and Jeff Bezos, is building specialized technology to enable sensory processing in computers. Google has acquired a handful of robotics companies as well as the AI startup DeepMind, and of course hired renowned futurist Ray Kurzweil as a director of engineering. The government’s Intelligence Advanced Research Projects Activity (IARPA) is building what could be interpreted as a backbone reminiscent of DARPA’s early Internet efforts, but for intelligent machines.

Nobody can predict the exact trajectory of all this R&D. It does, however, pave the road for a very different world from the one we know today.

The Robots Aren’t Attacking, But You Should Pay Attention

We’re just beginning to understand and frame the implications of cognitive technology. In roughly a decade, machine intelligence has gone from a niche-dwelling corporate and academic tool to something that will help us drive our cars.

As our eyes open to the implications, concern is bubbling up in popular discourse. Will robots take our jobs? Where are big data’s boundaries in terms of privacy?

We’re still close to the beginning of the evolution of machine intelligence. While it’s worth discussing its implications in advance, the technology isn’t advanced enough for, say, robots to create a state of mass unemployment.

What is worthy of attention is the Darwinistic effect that machine intelligence is driving, right now, for the average business—both enterprise and small- to medium-sized businesses (SMBs). Commerce is becoming a matter of “use data or lose your edge.” Those relying exclusively on human intuition or human activity will lose out to some extent.

Enterprises end up with so much data that it becomes impossible to handle it without machine intelligence. Amazon or Walmart have too many SKUs to decide on each item’s price on a daily basis, and so rely on analytics software for dynamic pricing. Corporate marketers have come to rely on analytics to prove the ROI of their campaigns to executives; financial firms depend on high-frequency trading to optimize their own investments.

Some SMBs, meanwhile, rely on human calculations in areas where the competition is gaining insight with algorithmic intelligence. A company that uses analytics to understand its entire customer lifecycle, from acquisition to upsell to churn, will better customize its offerings than the business that works off assumptions. Likewise, a company that uses analytics to understand its marketing ecosystem will work faster than one that manually sifts through channels.  

Working with Smart Machines, Incrementally

Charles Darwin once said that “it is not the strongest or most intelligent who will survive, but those who can best manage change.” Software has moved from a simple functionary into a more complex advisory role, presenting evidence to influence human decision-making across industries. Businesses are already using machine intelligence to assist with their operation, creating a new wave of digitally assisted commerce.

For those businesses that are laggards in integrating the new role of computers, it’s not a matter of if they will adopt, but when. As machines gain momentum and industry leaders integrate them en force, the message is clear: the sooner, the better.

Marius Moscovici is the Founder & CEO of Metric Insights




Edited by Alisen Downey
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