Future of Work

Here’s how one of Google’s top scientists thinks people should prepare for machine learning

Peter Norvig, Director of Research at Google.
Source: Stevens Institute of Technology

People like famed physicist Stephen Hawking and Tesla's Elon Musk have issued dark warnings of a world where computers become so sophisticated, so quickly, that humanity loses control of them—and its own destiny as a result.

Yet Peter Norvig, a leading artificial intelligence scientist and a director of research at Google, thinks that's far-fetched. "I don't buy into the killer robot [theory]," he told CNBC this week.

The real worry is how to prepare for the mass elimination of jobs that is surely coming, he said.

"I certainly see that there will be disruptions in employment … we've already seen a lot of change, that's going to continue," Norvig said in an interview, before a lecture on machine learning at the Stevens Institute of Technology.

By now there's wide consensus on this matter, the question is really just scale — whether the impact of machine learning is minimal or whether it consumes half of all jobs over the next decade.

Although this process is well underway with manufacturing jobs, more and more it's going to creep up the value chain, altering or eliminating any number of jobs in law, finance and even media.

"The pace may be so fast that it [will] cause disruptions," Norvig said. "So we need to find ways to mitigate that."

Be aware of the various technologies and be able to use them, and apply them to whatever field you're interested in.
Peter Nordvig
research director, Google

Norvig, a former computer scientist as NASA, sympathized with anyone frightened by the prospect. "It is scary," he said.

But just as the internal combustion engine ultimately led to the demise of the stagecoach, and also to millions of new jobs, so will these destructive technologies lead to new opportunities that are now unimagined.

"It's easy to see jobs disappearing ... [but] it's hard to see the new jobs that will be invented because they don't exist yet.

"There will always be stuff to do," he said.

Young people starting on their career path shouldn't necessarily be discouraged by machine learning, or abandon career aspirations because of it, Norvig said.

Instead, "find something [you're] interested in that provides something that people want, and think deeply about it."

"Be aware of the various technologies and be able to use them, and apply them to whatever field you're interested in," he added.

Norvig also believes the rest of society has an obligation to support—either through universal basic income, a WPA-like program, or some other means—people whose livelihoods are eliminated so quickly that they are unable to adapt.

"There has to be some social program for people who say 'I had a job, and now I don't—I've got no family to fall back on, what do I do?'" he said.