Book summary: AI Superpowers

THE VIEW FROM BEIJING

What you saw in this match depended on where you watched it from. To some observers in the United States, AlphaGo’s victories signaled not just the triumph of machine over man but also of Western technology companies over the rest of the world.

But looking out my office window during the Ke Jie match, I saw something far different. The headquarters of my venture-capital fund is located in Beijing’s Zhongguancun (pronounced “jong-gwan-soon”) neighborhood, an area often referred to as “the Silicon Valley of China.”

To people here, AlphaGo’s victories were both a challenge and an inspiration. They turned into China’s “Sputnik Moment” for artificial intelligence.

When Chinese investors, entrepreneurs, and government officials all focus in on one industry, they can truly shake the world. Indeed, China is ramping up AI investment, research, and entrepreneurship on a historic scale.

And less than two months after Ke Jie resigned his last game to?AlphaGo, the Chinese central government issued an ambitious plan?to build artificial intelligence capabilities. It called for greater funding, policy support, and national coordination for AI development.

It set clear benchmarks for progress by 2020 and 2025, and it projected that by 2030 China would become the center of global innovation in artificial intelligence, leading in theory, technology, and application.

By 2017, Chinese venture-capital investors had already responded to that call, pouring record sums into artificial intelligence startups and making up 48 percent?of all AI venture funding globally, surpassing the United States for the first time.

AI AND INTERNATIONAL RESEARCH

American universities and technology companies have for decades reaped the rewards of the country’s ability to attract and absorb talent from around the globe. Progress in AI appeared to be no different. The United States looked to be out to a commanding lead,?one that would only grow as these elite researchers leveraged Silicon Valley’s generous funding environment, unique culture, and powerhouse companies.

In the eyes of most analysts, China’s technology industry was destined to play the same role in global AI that it had for decades: that of the copycat who lagged far behind the cutting edge.

As I demonstrate in the following chapters, that analysis is wrong. It is based on outdated assumptions about the Chinese technology environment, as well as a more fundamental misunderstanding of what is driving the ongoing AI revolution.

The West may have sparked the fire of deep learning, but China will be the biggest beneficiary of the heat the AI fire is generating. That global shift is the product of two transitions: from the age of discovery to the age of implementation, and from the age of expertise to the age of data.

ADVANTAGE CHINA

Harnessing the power of AI today—the “electricity” of the twenty-first century—requires four analogous inputs: abundant data, hungry entrepreneurs, AI scientists, and an AI-friendly policy?environment.

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.

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 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.

THE HAND ON THE SCALES

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

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. Further concentrating those profits is the fact that AI naturally trends toward winner-take-all economics within an industry. 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.

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.

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.

CONTRASTING CULTURES

Entrepreneurs in the valley are often the children of successful professionals, such as computer scientists, dentists, engineers, and academics. Growing up they were constantly told that they—yes,?they?in particular—could change the world. Their undergraduate years were spent learning the art of coding from the world’s leading researchers but also basking in the philosophical debates of a liberal arts education.

It’s an environment of abundance that lends itself to lofty thinking, to envisioning elegant technical solutions to abstract problems. Central to that ideology is a wide-eyed techno-optimism, a belief that every person and company can truly change the world through innovative thinking. Copying ideas or product features is frowned upon as a betrayal of the zeitgeist and an act that is beneath the moral code of a true entrepreneur.

Startups that grow up in this kind of environment tend to be?mission-driven.?They start with a novel idea or idealistic goal, and they build a company around that. Company mission statements are clean and lofty, detached from earthly concerns or financial motivations.

In stark contrast, China’s startup culture is the yin to Silicon?Valley’s yang: instead of being mission-driven, Chinese companies are first and foremost?market-driven.?

The core motivation for China’s market-driven entrepreneurs is not fame, glory, or changing the world. Those things are all nice side benefits, but the grand prize is getting rich, and it doesn’t matter how you get there.

Jarring as that mercenary attitude is to many Americans, the Chinese approach has deep historical and cultural roots. Rote memorization formed the core of Chinese education for millennia. Entry into the country’s imperial bureaucracy depended on word-for-word memorization of ancient texts and the ability to construct a perfect “eight-legged essay” following rigid stylistic guidelines.

While Socrates encouraged his students to seek truth by questioning everything, ancient Chinese philosophers counseled people to follow the rituals of sages from the ancient past. Rigorous copying of perfection was seen as the route to true mastery.

Layered atop this cultural propensity for imitation is the deeply ingrained scarcity mentality of twentieth-century China. Most Chinese tech entrepreneurs are at most one generation away from grinding poverty that stretches back centuries.

Many are only children—products of the now-defunct “One Child Policy”—carrying on their backs the expectations of two parents and four grandparents who have invested all their hopes for a better life in this child. Growing up, their parents didn’t talk to them about changing the world. Rather, they talked about survival, about a responsibility to earn money so they can take care of their parents when their parents are too old to work in the fields.

The blistering pace of China’s economic rise hasn’t alleviated that scarcity mentality. Chinese citizens have watched as industries, cities, and individual fortunes have been created and lost overnight in a Wild West environment where regulations struggled to keep pace with cutthroat market competition.

For years, the copycat products that emerged from China’s cultural stew were widely mocked by the Silicon Valley elite. But those outsiders missed what was brewing beneath the surface. The most valuable product to come out of China’s copycat era wasn’t a product at all: it was the entrepreneurs themselves

WHY SILICON VALLEY GIANTS FAIL IN CHINA

American companies treat China like just any other market to check off their global list. They don’t invest the resources, have the patience, or give their Chinese teams the flexibility needed to compete with China’s world-class entrepreneurs. They see the primary job in China as?marketing?their existing products to Chinese users. In reality, they need to put in real work?tailoring?their products for Chinese users or?building?new products from the ground up to meet market demands.

Resistance to localization slows down product iteration and makes local teams feel like cogs in a clunky machine.

With so much opportunity now for growth within Chinese startups, the most ambitious young people join or start local companies. They know that if they join the Chinese team of an American company, that company’s management will forever see them as “local hires,” workers whose utility is limited to their country of birth. They’ll never be given a chance to climb the hierarchy at the Silicon Valley headquarters, instead bumping up against the ceiling of a “country manager” for China.

The most ambitious young people—the ones who want to make a global impact—chafe at those restrictions, choosing to start their own companies or to climb the ranks at one of China’s tech juggernauts.

Battles with Silicon Valley may have created some of China’s homegrown internet Goliaths, but it was cutthroat Chinese domestic competition that forged a generation of gladiator entrepreneurs.

INNOVATION FOR THE MASSES

On September 10, 2014, Premier Li Keqiang took the stage during the 2014 World Economic Forum’s “Summer Davos” in the coastal Chinese city of Tianjin. There he spoke of the crucial role technological innovation played in generating growth and modernizing the Chinese economy. The speech was long and dense, heavy on jargon and light on specifics. But of note during the speech, Li repeated a phrase that was new to the Chinese political lexicon: “mass entrepreneurship and mass innovation.”

Nine months after Li’s speech, China’s State Council—roughly equivalent to the U.S. president’s cabinet—issued a major directive on advancing mass entrepreneurship and innovation. It called for the creation of thousands of technology incubators, entrepreneurship zones, and government-backed “guiding funds” to attract greater private venture capital.

Larger city and provincial governments pioneered different models for “guiding funds,” a mechanism that uses government money to spur more venture investing. The funds do that by increasing the upside for private investors without removing the risk.

The government uses money from the guiding fund to invest in private venture-capital funds in the same role as other private limited partners. If the startups that fund invested in (the “portfolio companies”) fail, all the partners lose their investment, including the government.

But if the portfolio companies succeed—say, double in value within five years—then the fund’s manager caps the government’s upside from the fund at a predetermined percentage, perhaps 10 percent, and uses private money to buy the government’s shares out at that rate. That leaves the remaining 90 percent gain on the government’s investment to be distributed among private investors who have already seen their own investments double.

Private investors are thus incentivized to follow the government’s lead, investing in funds and industries that the local government wants to foster.

During China’s mass innovation push, use of local government guiding funds exploded, nearly quadrupling?from $7 billion in 2013 to $27 billion in 2015.

American policy analysts and investors looked askance at this heavy-handed government intervention in what are supposed to be free and efficient markets. Private-sector players make better bets when it comes to investing, they said, and government-funded innovation zones or incubators will be inefficient, a waste of taxpayer money.

But what these critics miss is that this process can be both highly inefficient and extraordinarily effective. When the long-term upside is so monumental, overpaying in the short term can be the right thing to do. The Chinese government wanted to engineer a fundamental shift in the Chinese economy, from manufacturing-led growth to innovation-led growth, and it wanted to do that in a hurry.

China’s top leadership did not have the patience to wait. It wanted to use government money to brute-force a faster transformation, one that would pay dividends through an earlier transition to higher-quality growth. That process of pure force was often locally inefficient—incubators that went unoccupied and innovation avenues that never paid off—but on a national scale, the impact was tremendous.

THE STUFF OF AN AI SUPERPOWER

As artificial intelligence filters into the broader economy, this era will reward the?quantity?of solid AI engineers over the?quality?of elite researchers.

Real economic strength in the age of AI implementation won’t come just from a handful of elite scientists who push the boundaries of research.

It will come from an army of well-trained engineers who team up with entrepreneurs to turn those discoveries into game-changing companies.

While America still dominates when it comes to superstar researchers, Chinese companies and research institutions have filled their ranks with the kind of well-trained engineers that can power this era of AI deployment.

Chinese students of AI are no longer straining in the dark to read outdated textbooks. They’re taking advantage of AI’s open research culture to absorb knowledge straight from the source and in real time. That means dissecting the latest online academic publications, debating the approaches of top AI scientists in WeChat groups, and streaming their lectures on smartphones.

Behind these efforts lies a core difference in American and Chinese political culture: while America’s combative political system aggressively punishes missteps or waste in funding technological upgrades, China’s techno-utilitarian approach rewards proactive investment and adoption.

Neither system can claim objective moral superiority, and the United States’ long track record of both personal freedom and technological achievement is unparalleled in the modern era. But I believe that in the age of AI implementation the Chinese approach will have the impact of accelerating deployment, generating more data, and planting the seeds of further growth. It’s a self-perpetuating cycle, one that runs on a peculiar alchemy of digital data, entrepreneurial grit, hard-earned expertise, and political will.

THE CHIP ON CHINA’S SHOULDER

One underdiscussed area of AI competition—among the AI giants, startups, and the two countries—is in computer chips, also known as semiconductors. High-performance chips are the unsexy, and often unsung, heroes of each computing revolution.

But from an economic and security perspective, building those chips is a very big deal: the markets tend toward lucrative monopolies, and security vulnerabilities are best spotted by those who work directly with the hardware.

Now, as traditional computing programs are displaced by the operation of AI algorithms, requirements are once again shifting. Machine learning demands the rapid-fire execution of complex mathematical formulas, something for which neither Intel’s nor Qualcomm’s chips are built.

Into the void stepped Nvidia, a chipmaker that had previously excelled at graphics processing for video games. The math behind graphics processing aligned well with the requirements for AI, and Nvidia became the go-to player in the chip market. Between 2016 and early 2018, the company’s stock price multiplied by a factor of ten.

These chips are central to everything from facial recognition to self-driving cars, and that has set off a race to build the next-generation AI chip. Google and Microsoft—companies that had long avoided building their own chips—have jumped into the fray, alongside Intel, Qualcomm, and a batch of well-funded Silicon Valley chip?startups.

The Chinese government has for many years—decades, even—tried to build up indigenous chip capabilities. But constructing a high-performance chip is an extremely complex and expertise-intensive process, one that has so far remained impervious to several government-sponsored projects.

Chinese leaders and a raft of chip startups are hoping that this time is different. The Chinese Ministry of Science and Technology is doling out large sums of money, naming as a specific goal the construction of a chip with performance and energy efficiency twenty times better than one of Nvidia’s current offerings.

On balance, Silicon Valley remains the clear leader in AI chip development. But it’s a lead that the Chinese government and the country’s venture-capital community are trying their best to erase.

That’s because when economic disruption occurs on the scale promised by artificial intelligence, it isn’t just a business question—it’s also a major political question.

THE FOUR WAVES OF AI

But it won’t happen all at once. The complete AI revolution will take a little time and will ultimately wash over us in a series of four waves: internet AI, business AI, perception AI, and autonomous AI. Each of these waves harnesses AI’s power in a different way, disrupting different sectors and weaving artificial intelligence deeper into the fabric of our daily lives.

These four waves all feed off different kinds of data, and each one presents a unique opportunity for the United States or China to seize the lead.

We’ll see that China is in a strong position to lead or co-lead in internet AI and perception AI, and will likely soon catch up with the United States in autonomous AI. Currently, business AI remains the only arena in which the United States maintains clear leadership.

THE AUTONOMOUS BALANCE OF POWER

While all of this may sound exciting and innovative to the Chinese landscape, the hard truth is that no amount of government support can guarantee that China will lead in autonomous AI.

It’s a problem that requires a core team of world-class engineers rather than just a broad base of good ones. This tilts the playing field back toward the United States, where the best engineers from around the globe still cluster at companies like Google.

Silicon Valley companies also have a substantial head start on research and development, a product of the valley’s proclivity for moonshot projects. Google began testing its self-driving cars as early as 2009, and many of its engineers went on to found early self-driving startups. China’s boom in such startups really didn’t begin until around 2016.

But even with that rapid catch-up by Chinese players, there’s no question that as of this writing, the most experienced self-driving technologists still call America home.

At this point, we just don’t yet know where that bottleneck will be, and fourth-wave AI remains anyone’s game.

While today the United States enjoys a commanding lead (90–10), in five years’ time I give the United States and China even odds of leading the world in self-driving cars, with China having the edge in hardware-intensive applications such as autonomous drones.

The balance of capabilities between the United States and China across the four waves of AI, currently and estimated for five years in the future

THE REAL AI CRISIS

Beyond direct job losses, artificial intelligence will exacerbate global economic inequality. By giving robots the power of sight and the ability to move autonomously, AI will revolutionize manufacturing, putting third-world sweatshops stocked with armies of low-wage workers out of business.

The large populations of young workers that once comprised the greatest advantage of poor countries will turn into a net liability, and a potentially destabilizing one. With no way to begin the development process, poor countries will stagnate while the AI superpowers take off.

But even within those rich and technologically advanced countries, AI will further cleave open the divide between the haves and the have-nots. The positive-feedback loop generated by increasing amounts of data means that AI-driven industries naturally tend toward monopoly, simultaneously driving down prices and eliminating competition among firms.

This concentration of economic power in the hands of a few will rub salt in the open wounds of social inequality.

In most developed countries, economic inequality and class-based resentment rank among the most dangerous and potentially explosive problems. The past few years have shown us how a cauldron of long-simmering inequality can boil over into radical political upheaval. I believe that, if left unchecked, AI will throw gasoline on the socioeconomic fires.

Lurking beneath this social and economic turmoil will be a psychological struggle, one that won’t make the headlines but that could make all the difference.

As more and more people see themselves displaced by machines, they will be forced to answer a far deeper question: in an age of intelligent machines, what does it mean to be human?

A TRIAL BY FIRE AND THE NEW SOCIAL CONTRACT

We are already witnessing the way that stagnant wages and growing inequality can lead to political instability and even violence. As AI rolls out across our economies and societies, we risk aggravating and quickening these trends. Labor markets have a way of balancing themselves out in the long run, but getting to that promised long run requires we first pass through a trial by fire of job losses and growing inequality that threaten to derail the process.

Building societies that thrive in the age of AI will require substantial changes to our economy but also a shift in culture and values.

Centuries of living within the industrial economy have conditioned many of us to believe that our primary role in society (and even our identity) is found in productive, wage-earning work. Take that away and you have broken one of the strongest bonds between a person and his or her community.

As we transition from the industrial age to the AI age, we will need to move away from a mindset that equates work with life or treats humans as variables in a grand productivity optimization algorithm.

No economic or social policy can “brute force” a change in our hearts. But in choosing different policies, we can reward different behaviors and start to nudge our culture in different directions.

LOOKING FORWARD AND LOOKING AROUND

The AI superpowers of the United States and China may be the countries with the expertise to build these technologies, but the paths to true human flourishing in the AI age will emerge from people in all walks of life and from all corners of the world.

As we look forward into the future, we must also take the time to look around.

As both the creative and disruptive force of AI is felt across the world, we need to look to each other for support and inspiration. The United States and China will lead the way in economically productive applications of AI, but other countries and cultures will certainly continue to make invaluable contributions to our broader social evolution.

No single country will have all the answers to the tangled web of issues we face, but if we draw on diverse sources of wisdom, I believe there is no problem that we can’t tackle together.

This wisdom will include pragmatic reforms to our education systems, subtle nuances in cultural values, and deep shifts in how we conceive of development, privacy, and governance.