Visitors to henn-na, a restaurant outside Nagasaki, Japan, are greeted by a peculiar sight: their food being prepared by a row of humanoid robots that bear a passing resemblance to the Terminator. The “head chef.” incongruously named Andrew, specializes in okonomiyaki, a Japanese pancake. Using his two long arms, he stirs batter in a metal bowl, then pours it onto a hot grill. While he waits for the batter to cook, he talks cheerily in Japanese about how much he enjoys his job. His robot colleagues, meanwhile, fry donuts, layer soft-serve ice cream into cones, and mix drinks. One made me a gin and tonic.
H.I.S., the company that runs the restaurant, as well as a nearby hotel where robots check guests into their rooms and help with their luggage, turned to automation partly out of necessity. Japan’s population is shrinking, and its economy is booming; the unemployment rate is currently an unprecedented 2.8 percent. “Using robots makes a lot of sense in a country like Japan, where it’s hard to find employees.” CEO Hideo Sawada told me.
Sawada speculates that 70 percent of the jobs at Japan’s hotels will be automated in the next five years. “It takes about a year to two years to get your money back.” he said. “But since you can work them 24 hours a day, and they don’t need vacation, eventually it’s more cost-efficient to use the robot.”
This may seem like a vision of the future best suited—perhaps only suited—to Japan. But according to Michael Chui, a partner at the McKinsey Global Institute, many tasks in the food-service and accommodation industry are exactly the kind that are easily automated. Chui’s latest research estimates that 54 percent of the tasks workers perform in American restaurants and hotels could be automated using currently available technologies—making it the fourth-most-automatable sector in the U.S.
The robots, in fact, are already here. Chowbotics, a company in Redwood City, California, manufactures Sally, a boxy robot that prepares salads ordered on a touch screen. At a Palo Alto café, I watched as she deposited lettuce, corn, barley, and a few inadvertently crushed cherry tomatoes into a bowl. Botlr, a robot butler, now brings guests extra towels and toiletries in dozens of hotels around the country. I saw one at the Aloft Cupertino.
One robot, Flippy, can flip 150 burgers an hour.
Robots have arrived in American restaurants and hotels for the same reasons they first arrived on factory floors. The cost of machines, even sophisticated ones, has fallen significantly in recent years, dropping 40 percent since 2005, according to the Boston Consulting Group. Labor, meanwhile, is getting expensive, as some cities and states pass laws raising the minimum wage.
The experience of Eatsa may be instructive. The start-up restaurant, based in San Francisco, allows customers to order its quinoa bowls and salads on their smartphone or an in-store tablet and then pick up their order from an eerie white wall of cubbies—an Automat for the app age. Initially, two greeters were stationed alongside the cubbies to welcome and direct customers. But over time, customers relied less frequently on the greeters, co-founder and CEO Tim Young told me, and the company now employs a single greeter in its restaurants.
The type of person who orders a grain bowl on an iPhone is perhaps content to forgo a welcoming human face. There may not be enough such people to sustain a business, however, at least not yet. Eatsa announced in October that it was closing its locations in New York City; Washington, D.C.; and Berkeley. Young told me that the problem was the food, not the technology, and that other restaurant chains are interested in deploying Eatsa’s model. The taco salad I ordered was pretty good, though, and, at $8, cheaper than the fare at many other salad chains. I wondered whether the problem wasn’t that Eatsa had crossed the fine line separating efficiency from something out of Blade Runner.
Less dystopian was the scene at Zume Pizza, in Mountain View, California, where I watched an assembly line of robots spread sauce on dough and lift pies into the oven. Thanks to its early investment in automation, Zume spends only 10 percent of its budget on labor, compared with 25 percent at a typical restaurant operation. The humans it does employ are given above-average wages and perks: Pay starts at $15 an hour and comes with full benefits; Zume also offers tuition reimbursement and tutoring in coding and data science. I talked with a worker named Freedom Carlson, who doesn’t have a college degree. She started in the kitchen, where she toiled alongside the robots. She has since been promoted to culinary-program administrator, and is learning to navigate the software that calculates nutritional facts for Zume pizzas.
That could be the case. James Bessen, an economist at Boston University School of Law, found that as the number of ATMs in America increased fivefold from 1990 to 2010, the number of bank tellers also grew. Bessen believes that ATMs drove demand for consumer banking: No longer constrained by a branch’s limited hours, consumers used banking services more frequently, and people who were unbanked opened accounts to take advantage of the new technology. Although each branch employed fewer tellers, banks added more branches, so the number of tellers grew overall. And as machines took over many basic cash-handling tasks, the nature of the tellers’ job changed. They were now tasked with talking to customers about products—a certificate of deposit, an auto loan—which in turn made them more valuable to their employers. “It’s not clear that automation in the restaurant industry will lead to job losses.” Bessen told me.
My experience with service bots was mixed. The day I visited the Aloft Cupertino, its robot butler was on the fritz. And when I asked Marriott’s new artificial-intelligence-powered chat system to look up my rewards number, it said it would get a human to help me with that. Neither interaction left me anticipating more-frequent hotel stays. As I wrote this column, however, Starbucks went from being a weekly splurge to a daily routine. The convenience of the app was difficult to pass up: I could place my order while on the bus and find my drink waiting for me when I got to the counter.
One day, I arrived at my local store to find that it had instituted a new policy requiring customers to retrieve mobile orders from a barista. (Apparently things can get a little hairy at the mobile-pickup station during rush hour at some stores.) I didn’t like the change; I’d grown accustomed to frictionless transactions. I started going to a different Starbucks location nearby, where I could pick up my coffee without the interference of a fellow human being.