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

by Kai-Fu Lee

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

Deep learning is what’s known as “narrow AI”—intelligence that takes data from one specific domain and applies it to optimizing one specific outcome. While impressive, it is still a far cry from “general AI,” the all-purpose technology that can do everything a human can.

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.

Much of the difficult but abstract work of AI research has been done, and it’s now time for entrepreneurs to roll up their sleeves and get down to the dirty work of turning algorithms into sustainable businesses.

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

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.

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.

These entrepreneurs will have access to the other “natural resource” of China’s tech world: an overabundance of data.

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.

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.

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.

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.

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

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 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.

In this sense, our current AI boom shares far more with the dawn of the Industrial Revolution or the invention of electricity than with the Cold War arms race.