Opinion | What China Can Teach the U.S. About Artificial Intelligence


In Silicon Valley, there is substantial stigma attached to imitating the business models or features of other companies. Doing so violates the “think different” ethos associated with innovators like Steve Jobs. The result is that pioneers often go unchallenged for long periods, allowed to dominate the industry even though they don’t explore or exploit all of their technology’s possibilities.

In contrast, Chinese entrepreneurs have few qualms about imitating what works. Once a concept is proved to have traction, dozens or even hundreds of other companies rush into the industry, setting off a ferocious fight for survival. The result is analogous to natural selection in evolution: All the companies start from the same branch on the family tree, but they make mutations in their product or business model to gain an edge. The companies with tweaked products that work well survive and grow, while businesses that are slow to adapt perish.

You can see this clearly in how the sharing economy developed in China. After companies like Uber and DiDi proved the viability of ride sharing, China’s start-up world tried out every possible iteration of it: shared basketballs, shared umbrellas, shared bicycles, shared mobile phone chargers. Most of these efforts died quickly, but those that survived — including a handful of the strongest shared-bike start-ups — turned into multibillion-dollar companies and revolutionized urban transport in just a couple of years.

Finally, there is the question of the Chinese government’s support of A.I. In the simplistic story often told in the United States, Chinese bureaucrats in the central government pick winners among the companies, load them up with enormous subsidies and then protect them from foreign competition. But this account fundamentally misunderstands how the Chinese government is encouraging A.I. implementation.

The Chinese government understands that as A.I. moves from affecting the purely digital world to the physical one, public infrastructure and institutions will have to change. If we want autonomous cars to reduce accidents, we may need to embed sensors in our roads. If we want A.I.-powered diagnosis to spot cancer earlier, we may need hospital administrators to develop data-sharing agreements that protect privacy while also allowing research to be conducted. These are decisions that entail a degree of risk for public actors, particularly in a highly combative political environment where every misstep becomes fodder for the opposition.

In declaring A.I. to be a top national priority, Beijing has sent a signal to local officials that they will be rewarded for fostering this kind of A.I. infrastructure. The Chinese model isn’t based on top-down orders or limitless subsidies; it’s based on encouraging local officials to make the changes needed in their area so that private A.I. companies can develop products that can actually be used.


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