by Kai-Fu Lee
Silicon Valley’s entrepreneurs have earned a reputation as some of the hardest working in America, passionate young founders who pull all-nighters in a mad dash to get a product out, and then obsessively iterate that product while seeking out the next big thing. Entrepreneurs there do indeed work hard. But I’ve spent decades deeply embedded in both Silicon Valley and China’s tech scene, working at Apple, Microsoft, and Google before incubating and investing in dozens of Chinese startups. I can tell you that Silicon Valley looks downright sluggish compared to its competitor across the Pacific.
China’s successful internet entrepreneurs have risen to where they are by conquering the most cutthroat competitive environment on the planet. They live in a world where speed is essential, copying is an accepted practice, and competitors will stop at nothing to win a new market. Every day spent in China’s startup scene is a trial by fire, like a day spent as a gladiator in the Coliseum. The battles are life or death, and your opponents have no scruples.
The only way to survive this battle is to constantly improve one’s product but also to innovate on your business model and build a “moat” around your company. If one’s only edge is a single novel idea, that idea will invariably be copied, your key employees will be poached, and you’ll be driven out of business by VC-subsidized competitors. This rough-and-tumble environment makes a strong contrast to Silicon Valley, where copying is stigmatized and many companies are allowed to coast on the basis of one original idea or lucky break. That lack of competition can lead to a certain level of complacency, with entrepreneurs failing to explore all the possible iterations of their first innovation. The messy markets and dirty tricks of China’s “copycat” era produced some questionable companies, but they also incubated a generation of the world’s most nimble, savvy, and nose-to-the-grindstone entrepreneurs. These entrepreneurs will be the secret sauce that helps China become the first country to cash in on AI’s age of implementation.
These entrepreneurs will have access to the other “natural resource” of China’s tech world: an overabundance of data. China has already surpassed the United States in terms of sheer volume as the number one producer of data. That data is not just impressive in quantity, but thanks to China’s unique technology ecosystem—an alternate universe of products and functions not seen anywhere else—that data is tailor-made for building profitable AI companies.
Until about five years ago, it made sense to directly compare the progress of Chinese and U.S. internet companies as one would describe a race. They were on roughly parallel tracks, and the United States was slightly ahead of China. But around 2013, China’s internet took a right turn. Rather than following in the footsteps or outright copying of American companies, Chinese entrepreneurs began developing products and services with simply no analog in Silicon Valley. Analysts describing China used to invoke simple Silicon Valley–based analogies when describing Chinese companies—“the Facebook of China,” “the Twitter of China”—but in the last few years, in many cases these labels stopped making sense. The Chinese internet had morphed into an alternate universe.
Chinese urbanites began paying for real-world purchases with bar codes on their phones, part of a mobile payments revolution unseen anywhere else. Armies of food deliverymen and on-demand masseuses riding electric scooters clogged the streets of Chinese cities. They represented a tidal wave of online-to-offline (O2O) startups that brought the convenience of e-commerce to bear on real-world services like restaurant food or manicures. Soon after that came the millions of brightly colored shared bikes that users could pick up or lock up anywhere just by scanning a bar code with their phones.
Tying all these services together was the rise of China’s super-app, WeChat, a kind of digital Swiss Army knife for modern life. WeChat users began sending text and voice messages to friends, paying for groceries, booking doctors’ appointments, filing taxes, unlocking shared bikes, and buying plane tickets, all without ever leaving the app. WeChat became the universal social app, one in which different types of group chats—formed with coworkers and friends or around interests—were used to negotiate business deals, organize birthday parties, or discuss modern art. It brought together a grab-bag of essential functions that are scattered across a dozen apps in the United States and elsewhere.
China’s alternate digital universe now creates and captures oceans of new data about the real world. That wealth of information on users—their location every second of the day, how they commute, what foods they like, when and where they buy groceries and beer—will prove invaluable in the era of AI implementation. It gives these companies a detailed treasure trove of these users’ daily habits, one that can be combined with deep-learning algorithms to offer tailor-made services ranging from financial auditing to city planning. It also vastly outstrips what Silicon Valley’s leading companies can decipher from your searches, “likes,” or occasional online purchases. This unparalleled trove of real-world data will give Chinese companies a major leg up in developing AI-driven services.
THE HAND ON THE SCALES
These recent and powerful developments naturally tilt the balance of power in China’s direction. But on top of this natural rebalancing, China’s government is also doing everything it can to tip the scales. The Chinese government’s sweeping plan for becoming an AI superpower pledged widespread support and funding for AI research, but most of all it acted as a beacon to local governments throughout the country to follow suit. Chinese governance structures are more complex than most Americans assume; the central government does not simply issue commands that are instantly implemented throughout the nation. But it does have the ability to pick out certain long-term goals and mobilize epic resources to push in that direction. The country’s lightning-paced development of a sprawling high-speed rail network serves as a living example.
Local government leaders responded to the AI surge as though they had just heard the starting pistol for a race, fully competing with each other to lure AI companies and entrepreneurs to their regions with generous promises of subsidies and preferential policies. That race is just getting started, and exactly how much impact it will have on China’s AI development is still unclear. But whatever the outcome, it stands in sharp contrast to a U.S. government that deliberately takes a hands-off approach to entrepreneurship and is actively slashing funding for basic research.
Putting all these pieces together—the dual transitions into the age of implementation and the age of data, China’s world-class entrepreneurs and proactive government—I believe that China will soon match or even overtake the United States in developing and deploying artificial intelligence. In my view, that lead in AI deployment will translate into productivity gains on a scale not seen since the Industrial Revolution. PricewaterhouseCoopers estimates AI deployment will add $15.7 trillion to global GDP by 2030. China is predicted to take home $7 trillion of that total, nearly double North America’s $3.7 trillion in gains. As the economic balance of power tilts in China’s favor, so too will political influence and “soft power,” the country’s cultural and ideological footprint around the globe.
This new AI world order will be particularly jolting to Americans who have grown accustomed to a near-total dominance of the technological sphere. For as far back as many of us can remember, it was American technology companies that were pushing their products and their values on users around the globe. As a result, American companies, citizens, and politicians have forgotten what it feels like to be on the receiving end of these exchanges, a process that often feels akin to “technological colonization.” China does not intend to use its advantage in the AI era as a platform for such colonization, but AI-induced disruptions to the political and economic order will lead to a major shift in how all countries experience the phenomenon of digital globalization.
THE REAL CRISES
Significant as this jockeying between the world’s two superpowers will be, it pales in comparison to the problems of job losses and growing inequality—both domestica
lly and between countries—that AI will conjure. As deep learning washes over the global economy, it will indeed wipe out billions of jobs up and down the economic ladder: accountants, assembly line workers, warehouse operators, stock analysts, quality control inspectors, truckers, paralegals, and even radiologists, just to name a few.
Human civilization has in the past absorbed similar technology-driven shocks to the economy, turning hundreds of millions of farmers into factory workers over the nineteenth and twentieth centuries. But none of these changes ever arrived as quickly as AI. Based on the current trends in technology advancement and adoption, I predict that within fifteen years, artificial intelligence will technically be able to replace around 40 to 50 percent of jobs in the United States. Actual job losses may end up lagging those technical capabilities by an additional decade, but I forecast that the disruption to job markets will be very real, very large, and coming soon.
Rising in tandem with unemployment will be astronomical wealth in the hands of the new AI tycoons. Uber is already one of the most valuable startups in the world, even while giving around 75 percent of the money earned from each ride to the driver. To that end, how valuable would Uber become if in the span of a couple of years, the company was able to replace every single human driver with an AI-powered self-driving car? Or if banks could replace all their mortgage lenders with algorithms that issued smarter loans with much lower default rates—all without human interference? Similar transformations will soon play out across industries like trucking, insurance, manufacturing, and retail.
Further concentrating those profits is the fact that AI naturally trends toward winner-take-all economics within an industry. Deep learning’s relationship with data fosters a virtuous circle for strengthening the best products and companies: more data leads to better products, which in turn attract more users, who generate more data that further improves the product. That combination of data and cash also attracts the top AI talent to the top companies, widening the gap between industry leaders and laggards.
In the past, the dominance of physical goods and limits of geography helped rein in consumer monopolies. (U.S. antitrust laws didn’t hurt either.) But going forward, digital goods and services will continue eating up larger shares of the consumer pie, and autonomous trucks and drones will dramatically slash the cost of shipping physical goods. Instead of a dispersion of industry profits across different companies and regions, we will begin to see greater and greater concentration of these astronomical sums in the hands of a few, all while unemployment lines grow longer.
THE AI WORLD ORDER
Inequality will not be contained within national borders. China and the United States have already jumped out to an enormous lead over all other countries in artificial intelligence, setting the stage for a new kind of bipolar world order. Several other countries—the United Kingdom, France, and Canada, to name a few—have strong AI research labs staffed with great talent, but they lack the venture-capital ecosystem and large user bases to generate the data that will be key to the age of implementation. As AI companies in the United States and China accumulate more data and talent, the virtuous cycle of data-driven improvements is widening their lead to a point where it will become insurmountable. China and the United States are currently incubating the AI giants that will dominate global markets and extract wealth from consumers around the globe.
At the same time, AI-driven automation in factories will undercut the one economic advantage developing countries historically possessed: cheap labor. Robot-operated factories will likely relocate to be closer to their customers in large markets, pulling away the ladder that developing countries like China and the “Asian Tigers” of South Korea and Singapore climbed up on their way to becoming high-income, technology-driven economies. The gap between the global haves and have-nots will widen, with no known path toward closing it.
The AI world order will combine winner-take-all economics with an unprecedented concentration of wealth in the hands of a few companies in China and the United States. This, I believe, is the real underlying threat posed by artificial intelligence: tremendous social disorder and political collapse stemming from widespread unemployment and gaping inequality.
Tumult in job markets and turmoil across societies will occur against the backdrop of a far more personal and human crisis—a psychological loss of one’s purpose. For centuries, human beings have filled their days by working: trading their time and sweat for shelter and food. We’ve built deeply entrenched cultural values around this exchange, and many of us have been conditioned to derive our sense of self-worth from the act of daily work. The rise of artificial intelligence will challenge these values and threatens to undercut that sense of life-purpose in a vanishingly short window of time.
These challenges are momentous but not insurmountable. In recent years, I myself faced a mortal threat and a crisis of purpose in my own personal life. That experience transformed me and opened my eyes to potential solutions to the AI-induced jobs crisis I foresee. Tackling these problems will require a combination of clear-eyed analysis and profound philosophical examination of what matters in our lives, a task for both our minds and our hearts. In the closing chapters of this book I outline my own vision for a world in which humans not only coexist alongside AI but thrive with it.
Getting ourselves there—on a technological, social, and human level—requires that we first understand how we arrived here. To do that we must look back fifteen years to a time when China was derided as a land of copycat companies and Silicon Valley stood proud and alone on the technological cutting edge.
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Copycats in the Coliseum
They called him The Cloner. Wang Xing (pronounced “Wang Shing”) made his mark on the early Chinese internet as a serial copycat, a bizarre mirror image of the revered serial entrepreneurs of Silicon Valley. In 2003, 2005, 2007, and again in 2010, Wang took America’s hottest startup of the year and copied it for Chinese users.
It all began when he stumbled on the pioneering social network Friendster while pursuing an engineering Ph.D. at the University of Delaware. The concept of a virtual network of friendships instantly clicked with Wang’s background in computer networking, and he dropped out of his doctoral program to return to China to recreate Friendster. On this first project, he chose not to clone Friendster’s exact design. Rather, he and a couple of friends just took the core concept of the digital social network and built their own user interface around it. The result was, in Wang’s words, “ugly,” and the site failed to take off.
Two years later, Facebook was storming college campuses with its clean design and niche targeting of students. Wang adopted both when he created Xiaonei (“On Campus”). The network was exclusive to Chinese college students, and the user interface was an exact copy of Mark Zuckerberg’s site. Wang meticulously recreated the home page, profiles, tool bars, and color schemes of the Palo Alto startup. Chinese media reported that the earliest version of Xiaonei even went so far as to put Facebook’s own tagline, “A Mark Zuckerberg Production,” at the bottom of each page.
Xiaonei was a hit, but one that Wang sold off too early. As the site grew rapidly, he couldn’t raise enough money to pay for server costs and was forced to accept a buyout. Under new ownership, a rebranded version of Xiaonei—now called Renren, “Everybody”—eventually raised $740 million during its 2011 debut on the New York Stock Exchange. In 2007, Wang was back at it again, making a precise copy of the newly founded Twitter. The clone was done so well that if you changed the language and the URL, users could easily be fooled into thinking they were on the original Twitter. The Chinese site, Fanfou, thrived for a moment but was soon shut down over politically sensitive content. Then, three years later Wang took the business model of red-hot Groupon and turned it into the Chinese group-buying site Meituan.
To the Silicon Valley elite, Wang was shameless. In the mythology of the valley, few things are more stigmatized than blindly aping the establishment.
It was precisely this kind of copycat entrepreneurship that would hold China back, or so the conventional wisdom said, and would prevent China from building truly innovative technology companies that could “change the world.”
Even some entrepreneurs in China felt that Wang’s pixel-for-pixel cloning of Facebook and Twitter went too far. Yes, Chinese companies often imitated their American peers, but you could at least localize or add a touch of your own style. But Wang made no apologies for his mimic sites. Copying was a piece of the puzzle, he said, but so was his choice of which sites to copy and his execution on the technical and business fronts.
In the end, it was Wang who would get the last laugh. By late 2017, Groupon’s market cap had shriveled to $2.58 billion, with its stock trading at under one-fifth the price of its 2011 initial public offering (IPO). The former darling of the American startup world had been stagnant for years and slow to react when the group-buying craze faded. Meanwhile, Wang Xing’s Meituan had triumphed in a brutally competitive environment, beating out thousands of similar group-buying websites to dominate the field. It then branched out into dozens of new lines of business. It is now the fourth most valuable startup in the world, valued at $30 billion, and Wang sees Alibaba and Amazon as his main competitors going forward.
