Summary:
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China is major in artificial intelligence (AI) research, development, and policy-making worldwide.
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China has been a critical player in the global network of artificial intelligence (AI) research and development (R&D) for more than 20 years, writing papers with foreign colleagues, hosting American corporate AI labs, and advancing the field worldwide.
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Part I presents the history of China’s AI development and its incredibly successful participation in worldwide R&D. It also explains how this history has aided China in becoming a world leader in the field.
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The article suggests rebalancing AI R&D with Chinese researchers and institutions using a risk-based approach in light of the problems brought on by these shifts.
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To balance the risks posed by China’s AI R&D with the benefits of an open research environment and strong international ties, such collaboration will require a clear assessment of costs and benefits.
China majors in artificial intelligence (AI) research, development, and policy-making worldwide. It is a leader in AI because it has a lot of intelligent people, is developing new technologies quickly, and spends a lot of money on research and development.
China has been a key player in the global network of artificial intelligence (AI) research and development (R&D) for more than 20 years, writing papers with foreign colleagues, hosting American corporate AI labs, and making progress in the field all over the world. Most policymakers didn’t pay much attention to these links and their effects for most of that time. Instead, the researchers, universities, and businesses that made these links decided what they were like.
But over the past five years, governments, universities, businesses, and members of civil society have looked at China’s connections to international R&D networks more closely. This reevaluation was prompted by four interconnected factors: (1) the growing capabilities of AI and its effects on both economic competitiveness and national security; (2) China’s unethical use of AI, including its use of AI tools for mass surveillance of its citizens, especially the Uyghur ethnic group in Xinjiang but also more widely; and (3) the rise in Chinese AI capabilities and ambitions, which make it a real competitor with the U.S. in AI.
These worries generated increased scrutiny and fresh inquiries about these enduring links. Does collaboration enable China to surpass democratic countries in AI? How much do tech workers and businesses from democratic countries help China set up tools that make life hard for people?
This working paper examines whether international AI collaboration with China is possible and how far it could go. Over the past two years, China has come up in conversations between government representatives and experts taking part in the Forum for Cooperation on AI (FCAI). In the 2021 FCAI progress report, the effects of China’s growth and how AI can be used for international cooperation are talked about. 1 The report was mainly about China’s policies and the benefits of AI that cause problems because of the country’s broader geopolitical, economic, and authoritarian policies. China mentioned a few recommendations about aligning regulations, developing standards, making trade deals, and doing R&D projects. During a roundtable discussion on December 8, 2021, participants in the FCAI were told more about these problems and asked for their thoughts.
This paper adds to and summarizes research that has already been done on how much China is involved in global AI R&D networks, what the benefits are, and what the possible drawbacks might be. Part I tells the story of how China developed AI and helped with research and development worldwide. It also explains how this history has helped China become a world leader. China and the United States have grown to be each other’s main collaborators, and China also collaborates closely with the other six FCAI participants. Part II demonstrates how China has integrated itself into global AI R&D networks. This collaboration happens in different ways, such as by attending university, attending conferences, writing joint papers, and working in research labs. Each has its own way of making, spreading, and using AI.
We discuss the problems and risks of cutting off the collaboration channels in Part III. We also give an overview of the economic, ethical, and strategic issues that make us wonder if this level of AI collaboration can continue. The report then considers potential developments in cooperation with China on AI R&D. It does this primarily by looking at the U.S. as a model, since the U.S. is by far China’s most prominent AI competitor and partner. It also provides a framework and a model for other countries and FCAI partners who work with China on AI R&D and face many of the same problems. Also, when trying to solve China’s problems, coordinated efforts are more likely to succeed than separate ones. Recent U.S. export restrictions on semiconductors and the manufacturing methods that go into them have exposed the crucial role that nations like Japan and Korea play. The U.S. government can now force foreign countries to follow U.S. laws by using administrative rules like the foreign direct product rule. But if foreign companies design U.S. technology out of their supply chains, these methods may be useless. Even though this work isn’t about hardware supply chains, the same things happen in both. As a result, this study discusses collaboration with China.
Coordination makes it more likely that solutions to China’s problems will work better than those done separately.
There are additional actors in this drama than the United States, other FCAI-participating states, and their allies. China’s actions will also influence the future of AI R&D in China. China’s growing desire for technical independence has made it easier for China to pull away from the global technology ecosystem in several ways, even though it is still deeply connected to other research networks around the world. How this relationship changes will depend significantly on what the Chinese government and Communist Party do now.
The article suggests rebalancing AI R&D with Chinese researchers and institutions using a risk-based approach in light of the problems brought on by these shifts. To find a good balance between the risks of China’s AI research and development and the benefits of an open research environment and strong international ties, a clear cost-benefit analysis will be needed. Most of the time, adopting a risk-based strategy won’t stop China’s AI research and development. Instead, it will require a rebalancing that takes into account the many ways that knowledge can be shared. Governments must work with businesses, universities, and research labs to understand the risks and benefits of AI research and development in China. Failure to incorporate these relationships into the risk assessment process could result in undesirable outcomes that incorrectly balance benefits and risks, making the United States worse.
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