China Is Using America’s Own Plan to Dominate the Future of Artificial Intelligence

China Is Using America’s Own Plan to Dominate the Future of Artificial Intelligence

The Chinese are massively investing in AI research and tech, while the Trump administration is cutting federal programs wholesale.


In late 2016, the Obama administration published three reports that shared an extraordinary conclusion: advances in machine learning, a technology that allows systems to learn and improve without explicit programming, are enabling a revolution in Artificial Intelligence (AI). As AI systems become increasingly capable of not only routine tasks like driving a car, but also complicated ones like designing car engines, AI technology will be the driving force behind transformations across both the economy and national security.

If imitation is the sincerest form of flattery, then the authors of the Obama administration reports have received a heartfelt compliment from their Chinese counterparts. With China’s July 2017 Next Generation Artificial Intelligence Development Plan, the country has announced that it, too, sees AI as the transformative technology that will underpin future economic and military power. China’s plan calls for exceeding all other nations in AI by 2030, but the checklist for China’s ambitious agenda is strikingly similar to the policies prescribed by the Obama administration’s reports. Greatly increase long-term investment in AI research and development (R&D)? Check. Promote collaboration on AI between the private tech sector and the government? Check. Develop a pipeline of top AI talent? Check. Invest to mitigate AI’s potential risks and societal disruptions? Check. The similarities go beyond such high-level objectives, even including many specific policy details and recommendations.

A reader of both documents would be forgiven for concluding that the Chinese strategy’s authors had copies of the White House reports on their desks as they wrote. Unlike a college term paper, however, there are no extra points for originality in governance. All that matters is to have the right policies and to implement them effectively. Unfortunately, there is plenty of reason to worry that China may have an edge in implementing policies practically cribbed from the United States.

The Obama administration sought to increase support for AI R&D, since annual federal funding for all computer science and mathematics R&D is less than half of what Google alone spends. Rather than boosting those levels, the Trump administration’s budget calls for cutting AI research at the National Science Foundation by 10 percent, to a mere $175 million. China, meanwhile, has demonstrated a willingness to spend jaw-dropping sums on technology when there are strategic national interests at play. For instance, in 2014, the Chinese government announced a 1 trillion RMB ($150 billion) investment fund to turn the Chinese semiconductor industry into a global powerhouse. Those figures are not merely hype. By 2017, the government had already made a third of that sum available. Similarly, China’s new plan foreshadows massive increases in funding for AI R&D.

One might think that U.S. government support for AI R&D is not terribly important, so long as U.S. companies lead the way. Perhaps that’s true in sectors like health care, but the U.S. companies with the best AI technology are often considerably less willing to invest in national security applications. When Google acquired DeepMind, arguably the world’s leading AI R&D organization, DeepMind required Google to prohibit the use of their research for military and government surveillance purposes. When Google acquired a leading military robotics developer, Google announced that the firm would no longer accept military contracts. And Google is far more cooperative with the national security community than most tech companies.

Chinese firms are less reluctant to make these distinctions. As China pursues a strategy of “military-civil fusion” in AI, it wields a range of policy mechanisms to incentivize industry cooperation. This summer, Tsinghua University — considered “China’s MIT” — announced plans to establish a Military-Civil Fusion lab that will provide a platform for dual-use advances in AI. Also this year, China established its first national deep-learning laboratory under the leadership of Baidu — often called “China’s Google” – and in partnership with the Chinese Academy of Sciences, Tsinghua University, and Beihang University. (Beihang University also happens to be a leader in the development of Chinese military aerospace technologies, including autonomous systems and robotics.)

No Chinese company has more enthusiastically embraced AI technology than Baidu. Despite lagging its U.S. and Chinese competitors in the mobile era, Baidu is reinventing itself around AI. Under the leadership of AI pioneer Andrew Ng, who until this March served as Baidu’s chief scientist and head of AI R&D, Baidu’s 1,300-person AI team achieved impressive results, developing better-than-human speech recognition software a year before Western companies and building out Baidu’s well-respected machine-learning cloud-infrastructure team. Ng’s departure was a significant setback, but Baidu remains focused on AI. Qi Lu, a former Microsoft executive and a leading AI specialist, has joined Baidu as chief operating officer.

Overall, Chinese tech companies are not as far behind as many in the West assume. This year, nearly all of the top-performing teams in the ImageNet Challenge, an influential AI competition, were from China. iFLYTEK, a Chinese AI startup, currently ranks second in the reading comprehension tasks measured by the Stanford Question Answering Dataset leaderboard, besting teams from Microsoft and Google, among others. While not yet the overall leaders in AI technology, Chinese researchers have proven their ability to catch up quickly and produce genuine innovation.

As China and other nations increasingly approach parity with the U.S. in key military technologies such as precision guided munitions and stealth aircraft, the Department of Defense hopes that AI will enable it to maintain military technological supremacy well into the 21st century. That’s a worthwhile goal, but achieving it will require that the United States not merely have a strategy, but also implement it better and faster than other countries. The Defense Department has sought to deepen ties with Silicon Valley to bring cutting-edge AI tech to the Pentagon, but even Defense Secretary James Mattis acknowledges that thus far the Pentagon has been challenged in these efforts.

Here too, China is embracing and implementing America’s strategy. Ng led Baidu’s AI efforts from the firm’s Silicon Valley campus. Since his departure, Baidu has announced plans to add a second site in the area. Tencent, the Chinese social media giant that both Facebook and Snapchat have confessed to imitating, has also moved in.

Chinese companies believe that by rotating Chinese staff to Silicon Valley and American staff to Chinese campuses, they can accelerate the timeline for reaching parity with the United States in AI technology and depth of talent. At present, however, the size and experience of China’s AI workforce remains dwarfed by that of the United States. Half of the top 10 employers of AI talent in China are U.S. firms, including IBM, Intel, and Microsoft, who may thus be integral to the development of China’s human capital in AI.

China’s copying of America’s homework could be a positive development if it deepens our understanding of the risks brought about by the rise of AI and how to mitigate them. The 2016 White House report addressed the workforce challenges of AI head on. Larry Summers, who served as Obama’s first director of the National Economic Council, predicts that the rise of AI in the economy could bring about “a third of men between the ages of 25 and 54 not working by the end of this half century.” Such an unemployment rate would be higher than that endured by Germany during the Great Depression when the Nazi Party came to power.

China’s AI plan likewise shows a clear understanding that increased automation is likely to reduce demand for labor across many sectors, putting societal stability (and perhaps the legitimacy and survival of the Communist Party) at risk. That’s why China’s strategy includes a call for a new regulatory focus on the ethical, security, and governance challenges of AI, including workforce displacement. Like the Obama plan, the Chinese plan also calls for government action to mitigate the economic pain and social instability of worker displacement. China’s government-led transition of hundreds of millions of laborers from agriculture to manufacturing shows that it has experience in this area, but for now its AI-related efforts remain at the planning stage. With official GDP growth rates still above 6 percent, China’s near-term problem is actually a labor shortage.

Unfortunately, the United States is no longer attempting to plan for these challenges. The current U.S. Treasury Secretary, Steve Mnuchin, has stated that AI workforce issues are “not even on our radar screen.” The White House Office of Science and Technology Policy (OSTP), which was instrumental in leading AI policy work during the Obama administration, has been essentially depleted of staff, with more than 70 out of 100 positions unfilled. The current administration has effectively deprived itself of critical expertise and insights on AI.

Without a recognition of the historic challenges of artificial intelligence — or a focus on preparing workers, soldiers, and diplomats for the future — will the United States be able to withstand AI’s disruptions or maintain competitiveness? Though China’s success in implementing its highly ambitious AI strategy remains to be seen, China’s actions are a clear indication of governmental commitment to this agenda at the highest levels. At this point, the United States is failing to implement the sensible and ambitious AI policy that the Obama administration left behind. Meanwhile, China is using the Obama playbook to stride boldly forward into the AI revolution.


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