By Invitation | The world after covid-19

Kai-Fu Lee on how covid spurs China’s great robotic leap forward

The pandemic is accelerating a shift towards people-less companies that will eventually characterise business everywhere

By Kai-Fu Lee

DURING THE SARS crisis almost 20 years ago, shops in Beijing were completely closed. It forced one retailer, Jingdong Century Trading Co, to try its luck online. That retailer was JD.com, today one of China’s e-commerce giants. Fast forward to 2020. Amid the covid-19 crisis, JD.com managed a 20% spike in sales with the help of a new, automated warehouse that can process more than 1.5m orders a day. In Wuhan, it delivered packages using robots and drones. It plans to open 1,000 automated restaurants this year across China.

The efforts are representative of a broader shift amid the pandemic towards automation, artificial intelligence and digitisation. The Chinese economy is undergoing a great robotic leap forward, as it removes human touch-points—literally—in its operations. Online businesses, algorithms and automation save costs, boost efficiency and protect public health. Though the shift predates covid-19, the crisis has accelerated it. Social distancing via automation will have wide-ranging implications. As goes China, so may go business everywhere.

People used to expect to interact with other people to get things done. No longer. Much work can be largely handed over to a combination of software and robotics. That’s true for blue-collar jobs in health care, food service, delivery, manufacturing, logistics, transport and education. And it is increasingly happening for back-office white-collar jobs in finance, customer service, sales, human resources, law and accounting.

Historically, automation tends to happen when economic difficulties coincide with maturing technologies. Companies feel they need to cut costs by slashing jobs and trying out new technologies. And once a company has replaced an employee with a robot and proven its efficacy, it is unlikely to go back. Robots don’t get sick. They don’t strike. They don’t demand higher wages for dangerous jobs. In fact, they are ideal for dangerous jobs, which in a pandemic is any job that requires interaction with people. It is no wonder that David Autor, an economist at MIT, calls the covid-19 pandemic and economic crisis “an automation-forcing event”.

China is uniquely positioned to lead the world in the automation economy. Though the country has a large workforce, the cost of labour has increased ten-fold in the last 20 years and is now more than twice as high as Vietnam’s. As the workshop of the world, it has an incentive to automate its manufacturing sector, which enjoys a lead on high-quality products. China is now the world’s largest market for industrial robotics and the fastest-growing, surging by 21% to $5.4bn in 2018. This represents a third of global sales. As a result, Chinese companies are developing a leg-up on the world in terms of how to work with metallic colleagues.

This has spilled over to domains beyond manufacturing. When the pandemic was spreading rapidly in Wuhan in February and the massive Huoshenshan Hospital was built in ten days, a fleet of robots was scurrying inside for disinfecting and delivering medical supplies. These machines are used across China in schools, hospitals and commercial buildings. Keenon, a robotics company in Shanghai, has developed an autonomous vehicle to disinfect areas, using a combination of LIDAR, machine vision and sensors.

Recently, when I was in quarantine at home in Beijing, all of my e-commerce packages and food were delivered by a robot in my apartment complex. The item would be placed on a sturdy, wheeled creature resembling R2D2. It could wirelessly summon the elevator, navigate autonomously to my door and then call my phone to announce its arrival. I could then take the delivery and the bot would return to reception.

A food-delivery firm, Meituan, has introduced a “zero contact” service, where the meals are delivered to specific drop-off points, but the driver and customer need never interact. The company is testing self-driving delivery vehicles. WeChat, a popular social-media and payment platform, has developed a system for people to use their phone to read a restaurant menu, order a meal and settle the bill, with either a human or a robot delivering the food to the table. Robot servers today are both gimmicks and safety measures, but tomorrow they may be a normal part of table service for most restaurants, save for posh ones.

However, the impact of automation is likely to be higher for white-collar jobs in the short term. Although basic, routine tasks like assembly-line work are easy to automate, much manual labour is hard for robots. “Intelligent automation” in the 21st century will be different from the rudimentary physical automation of the 20th century, since today’s robots require drawing together mechanical engineering, AI for perception and fine-motor manipulation. Yet as white-collar employees work from home during the pandemic, everything happens online and all tasks are translated into data, it is a small step to have machines take over completely. Companies offering “robotic process automation” are experiencing a boom in sales since the crisis began.

I’ve seen these trends develop as a technology investor in China—and had a front-row seat during lockdown. Zhuiyi Technology, a company in our portfolio, develops software for call-centre automation. During the pandemic, the credit-card department of a large Chinese bank used the system to call its customers, managing 350,000 calls a day, or the equivalent of 1,200 human customer-service representatives. These conversational bots not only reduce cost, but also improve customer satisfaction and boost revenue. The company has since expanded its range to include AI telemarketers, AI analysts, AI trainers, AI assistants and so on.

We can already see the contours of the post-covid business environment taking shape. Everything that can be cost-effectively automated will be, removing people from the process not just for profit and performance but for health and safety. If robots and software were appealing before the pandemic, the reasons not to adopt the technologies are even thinner now, whether a vaccine against covid-19 is developed or not.

Although automation changes some jobs and decimates others, many new jobs are created too. For example, the new digital infrastructure of data centres, 5G equipment, and software will need human workers, as will the operation and repair of robots. So will human-centric data collection and labelling, as the “fuel” that powers AI and facilitates an automation economy.

Many sectors will be reimagined in the form of human-digital symbiosis. In education, for example, AI will become the tutor and always-on instructor, while the human is the wise mentor and motivator. In healthcare, AI will be the accurate, targeted diagnosis engine that assists the human doctor, who communicates with patients and makes final decisions.

The public and private sectors need to work together on the transition to the automation economy. They must experiment and establish the best practices to prepare the workforce and retrain those at risk of unemployment. China’s early adoption of automation technologies—and its successful transition from an impoverished agrarian economy to an industrial powerhouse—means its experience offers valuable lessons.

After the second world war, American business practices became the global standard to which all companies around the world aspired. Accelerated by the pandemic, China will be the economy that drives automation, AI and robotics deep into businesses and industries, while showing the way for others to follow.
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Kai-Fu Lee is the chairman and chief executive of Sinovation Ventures in Beijing. A former executive at Google and Microsoft, he is the author of “AI Superpowers: China, Silicon Valley and the New World Order” (HMH, 2018).

This guest commentary is part of an occasional series on “The world after covid-19”. More articles can be found at Economist.com/by-invitation

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