AI Superpowers: China, Silicon Valley, and the New World Order

by Kai-Fu Lee

But more important, this shift will create an opportunity for all people to rediscover what it is that makes us human.

“Artificial intelligence is the elucidation of the human learning process, the quantification of the human thinking process, the explication of human behavior, and the understanding of what makes intelligence possible. It is men’s final step to understand themselves, and I hope to take part in this new, but promising science.”

Doing this requires massive amounts of relevant data, a strong algorithm, a narrow domain, and a concrete goal.

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.

What these researchers are doing requires great skill and deep knowledge: the ability to tweak complex mathematical algorithms, to manipulate massive amounts of data, to adapt neural networks to different problems.

Today, successful AI algorithms need three things: big data, computing power, and the work of strong—but not necessarily elite—AI algorithm engineers.

but in this age of implementation, data is the core.

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.

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.

but I forecast that the disruption to job markets will be very real, very large, and coming soon.

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.

The most valuable product to come out of China’s copycat era wasn’t a product at all: it was the entrepreneurs themselves.

By the end of 2017, 65 percent of China’s over 753 million smartphone users had enabled mobile payments.

Data on total trips through ride-hailing apps is somewhat scarce, but during the height of competition between Uber and Didi, self-reported numbers from the two companies had Didi’s rides in China at four times the total of Uber’s global rides.

As I laid out earlier, creating an AI superpower for the twenty-first century requires four main building blocks: abundant data, tenacious entrepreneurs, well-trained AI scientists, and a supportive policy environment.

That type of data collection may rub many Americans the wrong way. They don’t want Big Brother or corporate America to know too much about what they’re up to. But people in China are more accepting of having their faces, voices, and shopping choices captured and digitized. This is another example of the broader Chinese willingness to trade some degree of privacy for convenience.

It’s up to each country to make its own decisions on how to balance personal privacy and public data. Europe has taken the strictest approach to data protection by introducing the General Data Protection Regulation, a law that sets a variety of restrictions on the collection and use of data within the European Union.

Today, the greatest advantage of manufacturing in China isn’t the cheap labor—countries like Indonesia and Vietnam offer lower wages.

buruh indonesia memang sudah terkenal murah

But while these machines are automated, they are not autonomous. While they can repeat an action, they can’t make decisions or improvise according to changing conditions. Entirely blind to visual inputs, they must be controlled by a human or operate on a single, unchanging track. They can perform repetitive tasks, but they can’t deal with any deviations or irregularities in the objects they manipulate.

But by giving machines the power of sight, the sense of touch, and the ability to optimize from data, we can dramatically expand the number of tasks they can tackle.

In China, the government’s proactive approach is to transform that conquest into coevolution.

If the latter scenario unfolds, China’s tech giants wouldn’t dominate the world, but they would play a role everywhere, improve their own algorithms using training data from many markets, and take home a substantial chunk of the profits generated.

Chinese and American internet companies have taken different approaches to winning local markets, and as these AI services filter out to every corner of the world, they may engage in proxy competition in countries like India, Indonesia, and parts of the Middle East and Africa.

AI proxy war

Superintelligence would be the product of human creation, not natural evolution, and thus wouldn’t have the same instincts for survival, reproduction, or domination that motivate humans or animals. Instead, it would likely just seek to achieve the goals given to it in the most efficient way possible.

A college degree—even a highly specialized professional degree—is no guarantee of job security when competing against machines that can spot patterns and make decisions on levels the human brain simply can’t fathom.

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.

In most developed countries, economic inequality and class-based resentment rank among the most dangerous and potentially explosive problems.

“Kai-Fu, humans aren’t meant to think this way. This constant calculating, this quantification of everything, it eats away at what’s really inside of us and what exists between us. It suffocates the one thing that gives us true life: love.”

I no longer think about what will be written on my tombstone. That’s not because I avoid thinking about death. I’m now more aware than ever that we all live in direct and constant relationship to our own mortality.

We are far from understanding the human heart, let alone replicating it. But we do know that humans are uniquely able to love and be loved, that humans want to love and be loved, and that loving and being loved are what makes our lives worthwhile.

To be clear, I do believe that education is the best long-term solution to the AI-related employment problems we will face.

These would include three broad categories: care work, community service, and education. These would form the pillars of a new social contract, one that valued and rewarded socially beneficial activities in the same way we currently reward economically productive activities.

the social investment stipend would nudge our culture in a more compassionate direction. It would put the economic bounty of AI to work in building a better society, rather than just numbing the pain of AI-induced job losses.

And once the full impact of AI—very good for productivity, very bad for employment—becomes clear, we should be able to muster the resources and public will to implement programs akin to the social investment stipend.

Let us choose to let machines be machines, and let humans be humans. Let us choose to simply use our machines, and more importantly, to love one another.