Kai-Fu Lee, the former head of Google research in China, told an audience at MIT last week that it will be white-collar workers, not their blue-collar counterparts, who see the first mass job-loss in response to automation technologies.
“This replacement is happening now, and it’s happening in a true, complete decimation,” Lee told a conference at MIT last week. “In my opinion, the white-collar workforce gets challenged first—blue-collar work later.”
Lee has backed Smart Finance Group, a company that uses machine learning to determine a person’s eligibility for a payday loan. Sinovation has also invested in companies that automate customer service, training, and other routine office services.
Lee also discussed what he sees as the four waves of automation:
“The first wave is being fueled by the availability of large quantities of labeled data. This has given big Internet companies, both in China and in the U.S., an advantage in building their businesses and cementing AI expertise.”
“The second wave—which is more relevant to the kind of workplace disruption Lee sees coming—is based on the availability of company data, especially in industries such as law and accounting. Law firms might need fewer paralegals, for instance, if machines can quickly and efficiently search through thousands of documents in researching a case.”
“A third wave relies on companies generating data through new products or apps, or by paying for it to be created.”
“And the fourth wave, still some way off, would bring fully automated services such as self-driving cars and robotic helpers.”
Discussions at the conference also shined a spotlight on the disagreement among experts as to the effect of automation on jobs as a whole, with some arguing that AI will dismantle certain jobs but create new ones in the process. Lee is less confident:
“Many optimists say in tech revolutions, jobs will go, jobs will come,” he said. “While there are places where jobs will be created, I’d say that’s the exception.”