President Donald Trump (left) with Chinese President Xi Jinping during a meeting of the G-20 summit in Osaka, Japan. Jinping’s emphasis on AI as part of his “China Dream” has a military aspect to it as well. | Susan Walsh/AP Photo global translations ‘We are being outspent. We are being outpaced’: Is America ceding the future of AI to China? POLITICO’s latest Global Translations podcast examines the economic, military and ethical stakes in the geopolitical rivalry over AI.

The last time a rival power tried to out-innovate the U.S. and marshaled a whole-of-government approach to doing it, the Soviet Union startled Americans by deploying the first man-made satellite into orbit. The Sputnik surprise in 1957 shook American confidence, galvanized its government and set off a space race culminating with the creation of NASA and the moon landing 50 years ago this month.

Two years since announcing a national plan to become the world leader in artificial intelligence by 2030, China is making progress toward its goal on an unprecedented scale, raising the question of whether America’s laissez-faire approach to technology is enough and whether another Sputnik moment is around the corner, according to interviews for the latest episode of POLITICO’s Global Translations podcast.


President Donald Trump in 2018 declared AI a national priority, and Lynne Parker, the White House coordinator on artificial intelligence policy, said America “is a very strong leader” in AI.

“If you look at industry output, if you look at the leading academic institutions that are leading the way and advancing the state of the art and AI, they’re American industries and they're American academics,” Parker said. “We're clearly producing the most impactful commercial products. And certainly that's not to say that the rest of the world isn't waking up to the great opportunities of AI — but clearly, the United States is in the lead.”

Meanwhile, Beijing has been pumping billions of dollars into research, supporting startups and retooling its education system from elementary schools to universities — all with an explicit goal of outpacing the U.S.

Governments around the world are taking notice.

“Over the last 10 years, there's been a big effort in China to become a world leader in research and in many areas — but one of them being computing — and I've seen computer science departments grow and grow until they are now on a par with departments in the West in terms of what the academics do and where they publish,” Dame Wendy Hall, professor of computer science at the University of Southampton and co-author of the U.K. government’s AI strategy, told the podcast.

The Chinese effort extends to regional and local governments, too. “The city of Tianjin alone plans to spend $16 billion on AI — and the U.S. government investment still totals several billion and counting. That’s still lower by an order of magnitude,” said Elsa Kania, an adjunct fellow with the Technology and National Security Program at the Center for a New American Security.

By her count, some 26 AI plans and policies have cropped up across 19 provinces and regions in China. “These tens of billions in local government spending far outshadows anything any city or state government in the U.S. is doing,” she said.

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Like the Soviet Sputnik, President Xi Jinping’s emphasis on AI as part of his “China Dream” has a military aspect to it as well.

“It's clear that AI has become an element of U.S.-China military competition and that the Chinese military sees this pursuit of intelligentization — or trying to leverage AI to enhance its military capabilities — as critical to achieving an advantage, perhaps even surpassing the U.S.,” said Kania, who studies Chinese military innovation.

Under pressure to compete on the AI front, the Trump administration last May issued an executive order that calls on the U.S. to improve research and development and come up with plans to maintain supremacy in innovation. “It's a multi-pronged approach that addresses a lot of areas such as AI R&D, making data more available, making computational resources more available, looking at education and workforce issues, AI governance issues, issues of technical standards and also issues of international engagement,” Parker said.

But critics worry it’s not nearly enough.

“We are being outspent. We are being out-researched. We are being outpaced. We are being out-staffed,” said Amy Webb, a professor at the NYU Stern School of Business who specializes in future forecasting. “We have failed and are continuing to fail to see China as a militaristic, economic, and diplomatic pacing threat when it comes to AI.”

Xi “sees artificial intelligence as an integral point in shifting geopolitics and geo-economics,” Webb said. China is spending 9 percent of its government budget on R&D — three times the U.S. level, she said. Meanwhile, in Washington, “there is a small group of people, they are having meetings and I have been to some of those meetings. And there is just no sense of urgency,” she said.

The rivalry is unfolding in tandem with Trump’s trade war with Beijing — which is itself, in part, an effort to force China to end forced technology transfers that have helped accelerate Chinese technological progress. And at stake are not only technological bragging rights, but military supremacy and control of technologies that can be used for authoritarian social control, according to interviews in the Global Translations podcast.

For example, AI-enabled facial recognition and voice recognition technology are part of an intensive surveillance system used to control China’s Muslim Uighur minority in the Xinjiang province — and that technology is being exported to other authoritarian regimes.

Such concerns have led to attempts at global governance. The Organization for Economic Cooperation and Development has put forth principles for standards and ethics to guide its development and deployment embraced by 41 countries, including the U.S.

The administration is continuing to work on a regulatory framework through Office of Management and Budget and the Office of Information and Regulatory Affairs, Parker said. “We always want to use AI in a way that's consistent with civil liberties and privacy and American values. So clearly we don't want to become a surveillance state like China,” she said. “On the other hand, the opposite extreme is to over-regulate to the point where we can't use it at all."

Critics like Webb say the U.S. market-based approach depends too much on the private sector.

“The problem with relying on the private sector and specifically companies like Google, Amazon, Facebook, Apple, IBM and Microsoft is that these are publicly traded companies. They have to turn a profit. So we've really put ourselves in kind of a preventable and also dangerous situation,” she said.

But the sheer scale of China’s brute-force effort should not be confused with results, cautions Parker. “The downside to having a centralized focused approach is that you get very quickly to an end goal that may be the wrong goal. The advantage of the American innovation ecosystem is that we allow many good ideas to be explored in depth and we can see which ones are going to be fruitful,” she said.

When the Soviets launched Sputnik, Washington vowed to never be surprised again — and the following year stood up DARPA, the Defense Advanced Research Projects Agency. The new agency was focused on long-term, game-changing research and funded projects that led to breakthroughs such as the internet, GPS, early self-driving cars and the beginnings of AI.

In 2018, the agency announced it was investing $2 billion on AI-related research over five years. While that’s a fraction of Chinese investment, John Everett, deputy director of the Information Innovation Office at DARPA, told the podcast he is not worried about another Sputnik-style surprise.

“Within this $2 billion that we're spending, it's across a very wide range of projects — no two of which are alike — and so we're placing a lot of strategic bets on technologies that may emerge in the future,” Everett said. “A lot of the money that‘s going into the research in China seems to be going into pattern recognition. So they will be able to do incrementally better pattern recognition by spending an enormous amount of money on it. But there's a declining return to incremental expenditures.”