Artificial intelligence already powers many of our interactions today. When you ask Siri for directions, peruse Netflix’s recommendations, or get a fraud alert from your bank, these interactions are led by computer systems using large amounts of data to predict your needs.
The market is only going to grow. By 2020, research firm IDC predicts, AI will help drive worldwide revenues to over $47 billion, up from $8 billion in 2016. Stanford adjunct professor Andrew Ng recently spoke at the Stanford Graduate School of Business and shared his views on the future of AI and what it means for industry, the workplace, and the U.S. educational system. Excerpts below:
Electricity changed how the world operated. It upended transportation, manufacturing, agriculture, health care. AI is poised to have a similar impact, he says. Information technology, web search, and advertising are already being powered by artificial intelligence. It decides whether we’re approved for a bank loan. It helps us order a pizza and estimate our wait time, and even tells the driver where to deliver it. Other areas ripe for AI impact: fintech, logistics, health care, security, and transportation.
“Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don’t think AI will transform in the next several years,” Ng says.
What’s slowing down AI adoption? Two problems: scarcity of data and talent. For AI to be meaningful, companies need to feed their algorithms vast amounts of data, which isn’t always readily available. In fact, Ng says some large companies launch products for the payout of data, not revenue, and then later monetize it through a different product.
These companies are also engaging in a talent war for smart employees.
“I would say the most scarce resource today is actually talent, because AI needs to be customized for your business context,” Ng says. “You can’t just download an open-source package and apply it to your problem.”
Because of this job displacement, the U.S. would be wise to rethink its educational system. Automation in agriculture led the United States to overhaul its education system and develop the K-12 and university system we use today. Similarly, the U.S. must develop a way to reskill people whose jobs are taken by computer algorithms.
“I think government should give people a safety net, but pay the unemployed to study, to provide the structure to help the unemployed study, so as to increase the odds of gaining skills needed to re-enter the workforce.”