In October 1957, the Soviet Union launched the Earth’s first artificial satellite, Sputnik 1. The craft was no bigger than a beach ball, but it spurred the US into a frenzy of research and investment that would eventually put humans on the Moon. Sixty years later, the world might have had its second “Sputnik moment.” But this time, it’s not the US receiving the wake-up call, but China; and the goal is not the exploration of space, but the creation of artificial intelligence.

The second Sputnik arrived in the form of AlphaGo, the AI system developed by Google-owned DeepMind. In 2016, AlphaGo beat South Korean master Lee Se-dol at the ancient Chinese board game Go, and in May this year, it toppled the Chinese world champion, Ke Jie. Two professors who consult with the Chinese government on AI policy told The New York Times that these games galvanized the country’s politicians to invest in the technology. And the report the pair helped shape — published last month — makes China’s ambitions in this area clear: the country says it will become the world’s leader in AI by 2030.

“It’s a very realistic ambition,” Anthony Mullen, a director of research at analyst firm Gartner, tells The Verge. “Right now, AI is a two-horse race between China and the US.” And, says Mullen, China has all the ingredients it needs to move into first. These include government funding, a massive population, a lively research community, and a society that seems primed for technological change. And it all invites the trillion-dollar question: in the coming AI Race, can China really beat the US?

Strength in numbers

To build great AI, you need data, and nothing produces data quite like humans. This mean’s China’s massive 1.4 billion population (including some 730 million internet users) might be its biggest advantage. These citizens produce reams of useful information that can be mined by the country’s tech giants, and China is also significantly more permissive when it comes to users’ privacy. For the purposes of building AI, this compares favorably with European countries and their “citizen-centric legislation,” says Mullen. Companies like Apple and Google are designing workarounds for this privacy problem, but it’s simpler not to bother in the first place.

China’s 1.4 billion population is a data gold mine for building AI

In China, this also means that AI is being deployed in ways that might not be acceptable in the West. For example, facial recognition technology is used for everything from identifying jaywalkers to dispensing toilet paper. These implementations seem trivial, but as any researcher will tell you, there’s no substitute for deploying tech in the wild for testing and developing. “I don’t think China will have the same level of existential crisis about the development of AI that the West will have,” says Mullen.

The adventures of Microsoft chatbots in China and the US make for a good comparison. In China, the company’s Xiaoice bot, which is downloadable as an app, has more than 40 million users, with regulars talking to it every night. It even published a book of poetry under a pseudonym, sparking a debate in the country about artificial creativity. By comparison, the American version of the bot, named Tay, was famously shut down in a matter of days after Twitter users taught it to be racist.

Matt Scott, CTO of Shenzhen machine vision startup Malong Technologies, says China’s attitude toward new technology can be “risk-taking” in a bracing way. “For AI you have to be at the cutting edge,” he says. “If you’re using technology that’s one year old, you’re outdated. And I definitely find that in China — at least, my community in China — is very adept at taking on these risks.”

A culture of collaboration

The output of China’s AI research community is, in some ways, easy to gauge. A report from the White House in October 2016 noted that China now publishes more journal articles on deep learning than the US, while AI-related patent submissions from Chinese researchers have increased 200 percent in recent years. The clout of the Chinese AI community is such that at the beginning of the year, the Association for the Advancement of Artificial Intelligence rescheduled the date of its annual meeting; the original had fallen on Chinese New Year.

What’s trickier, though, is knowing how these numbers translate to scientific achievement. Paul Scharre, a researcher at the think tank Center for a New American Security, is skeptical about statistics. “You can count the number of papers, but that’s sort of the worst possible metric, because it doesn’t tell you anything about quality,” he says. “At the moment, the real cutting-edge research is still being done by institutions like Google Brain, OpenAI, and DeepMind.”

In China, though, there is more collaboration between firms like these and universities and government — something that could be beneficial in the long term. Scott’s Malong Technologies runs a joint research lab with Tsinghua University, and there are much bigger partnerships like the “national laboratory for deep learning” run by Baidu and the Chinese government’s National Development and Reform agency.

Other aspects of research seem influential, but are difficult to gauge. Scott, who started working in machine learning 10 years ago with Microsoft, suggests that China has a particularly open AI community. “I think there is a bit more emphasis on [personal] relationships,” he says, adding that China’s ubiquitous messaging app WeChat is a rich resource, with chat groups centered around universities and companies sharing and discussing new research. “The AI communities are very, very alive,” he says. “I would say that WeChat as a vehicle for spreading information is highly effective.”

Remember: the government helped make the internet

What most worries Scharre is the US government’s current plans to retreat from basic science. The Trump administration’s proposed budget would slash funding for research, taking money away from a number of agencies whose work could involve AI. “Clearly [Washington doesn’t] have any strategic plan to revitalize American investment in science and technology,” Scharre tells The Verge. “I am deeply troubled by the range of cuts that the Trump administration is planning. I think they’re alarming and counterproductive.”

Trump’s administration could never be called “science-friendly”

The previous administration was aware of the dangers and potential of artificial intelligence. Two reports published by the Obama White house late last year spelled out the need to invest in AI, as well as touching on topics like regulation and the labor market. “AI holds the potential to be a major driver of economic growth and social progress,” said the October report, noting that “public- and private-sector investments in basic and applied R&D on AI have already begun reaping major benefits.”

In some ways, China’s July policy paper on AI mirrors this one, but China didn’t just go through a dramatic political upheaval that threatens to change its course. The Chinese policy paper says that by 2020 it wants to be on par with the world’s finest; by 2025 AI should be the primary driver for Chinese industry; and by 2030, it should “occupy the commanding heights of AI technology.” According to a recent report from The Economist, having the high ground will pay off, with consultancy firm PwC predicting that AI-related growth will lift the global economy by $16 trillion by 2030 — with half of that benefit landing in China.

Where do we go from here?

For Scharre, who recently wrote a report on the threat AI poses to national security, the US government is laboring under a delusion. “A lot of people take it for granted that the US builds the best tech in the world, and I think that’s a dangerous assumption to make,” he says, saying that a wake-up call is due. China may have had the “Sputnik moment” it needed to back AI, but has the US?

Others question whether this is necessary. Mullen says that while the momentum to be the world leader in AI currently lies with China, the US is still marginally ahead, thanks to the work of Silicon Valley. Scharre agrees, and says that government funding isn’t that big of an issue while US tech giants are able to redirect just a little of their ad money to AI. “Money you get from somewhere like DARPA is just a drop in the ocean compared to what you can get from the likes of Google and Facebook,” he says.

These companies also provide a counterpoint to the argument that China’s demographics give it an unmatchable advantage. It’s certainly good to have a huge number of users in one country, but it’s probably better to have that same number of users spread across the world. Both Facebook and Google have more than 2 billion people hooked on to their primary platforms (Facebook itself and Android) as well as a half-dozen other services with a billion-plus users. It’s arguable that this sort of reach is more useful, as it provides an abundance of data, as well as diversity. China’s tech companies may be formidable, but they lack this international reach.

Scharre suggests this is important, because when it comes to measuring progress in AI, on-the-ground implementations are worth more than research. What counts, he says, is “the ability of nations and organizations to effectively implement AI technologies. Look at things like using AI in healthcare diagnoses, in self-driving cars, in finance. It’s fine to be, say, 12 months behind in research terms, as long as you can still get ahold of the technology and use it effectively.”

In that sense, the AI race doesn’t have to be zero sum. Right now, cutting-edge research is developed in secret, but shared openly across borders. Scott, who has worked in the field in both the US and China, says the countries have more in common than they think. “People are afraid that this is something happening in some basement lab somewhere, but it’s not true,” he says. “The most advanced technology in AI is published, and countries are actively collaborating. AI doesn’t work in a vacuum: you need to be collaborative.”

In some ways, this is similar to the situation in 1957. When news of Sputnik’s launch first broke, there was an air of scientific respect, despite the the geopolitical rivalry between the US and USSR. A contemporary report said that America’s top scientists “showed no rancor at being beaten into space by the Soviet engineers, and, as one of them put it, ‘We are all elated that it is up there.’”

Throughout the ‘60s and early ‘70s, America and Russia jockeyed back and forth to be “first” in the space race. But in the end, the benefits of this competition — new scientific knowledge, technology, and culture — didn’t just go to the winner. They were shared more evenly than that. By this metric, a Sputnik moment doesn’t have to be cause for alarm, and the race to build better AI could still benefit us all.