Is AI more like electricity or more like PCs? Optimistically, AI could trigger a wave of productivity gains similar to the great electrification of the late 19th and early 20th centuries. Last year, researchers at Goldman Sachs predicted that AI could contribute up to 7% to the global economy by 2033.
But not everyone is buying the hype. In an April research paper, MIT economist Daron Acemoglu argued that AI will provide a much more modest boost to GDP, at just 1.1% over the next decade. Previous technological advances, like the PC and the internet, have generated more limited productivity gains compared to previous “industrial revolutions.”
But speakers at Fortune Brainstorm AI Singapore last week sought to reassure attendees that AI could really lead to productivity gains, at least for a while.
“People are underestimating the long-term impact of large-scale AI and overestimating the short-term impact,” said Panos Madamopoulos-Molaris, founding managing director of industry programs and partnerships at Stanford University's Institute for Human-Centered AI.
He warned that companies may have unrealistic expectations about when they'll see a return on their AI investments, saying it will take time for large companies to fully bring their AI operations online.
Anant Maheshwari, president and CEO of Honeywell's global high growth regions, suggested aviation could be an industry that AI can revolutionize.
He acknowledged that most people would be uncomfortable flying a fully autonomous plane on a long-haul flight, but AI could augment the capabilities of human pilots, allowing airlines to operate planes with fewer people, resulting in more flights overall.
“Today, it takes two pilots to fly a plane. Can we get that to zero? Probably not. But can we use AI to get that down to one and enable more flights? Yes, it can,” Masheshwari said.
Conversely, Maheshwari suggested that AI could also help countries with the opposite problem: a labor surplus rather than a labor shortage. Developing countries “need to train a lot of people for these new industries,” he said. “Again, they need AI to help workers get up the learning curve very quickly.”
Some critics worry that AI could cause mass unemployment as white-collar workers lose their jobs to automation: Last year, Goldman Sachs warned that AI could put 300 million full-time jobs at risk.
And companies are already using AI as a reason to lay off employees: In January, United Parcel Service cut 12,000 management positions, in what may have been the largest cut in the company's history. At the time, CEO Carol Tomé said AI was making the cuts possible, citing the example of how salespeople no longer need to consult with pricing experts to write proposals.
But Stanford University's Madamopoulos Moralis isn't too worried about AI replacing humans entirely, citing the concept of complementarity, saying humans will be better than AI at jobs that require emotional intelligence, creative problem-solving and contextual understanding.
And he pointed out that for many industries the problem isn't too few workers to do the job, but too many inefficient human workers.
“There's been a lot of discussion in the medical community about radiologists and how they're going to be replaced,” Madamopoulos-Moralis said. “And guess what? We don't have enough of them in the U.S. We actually have twice as many openings as usual to work as radiologists.”
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