3.Centralization. Err neg---their ev overlooks Chinese censorship and overregulation, which limit the utility of innovation.

Chinese AI developers struggle with the pressure to keep up with their U.S. counterparts. In August 2021, more than 100 researchers at Stanford collaborated on a major paper about the future of so-called foundation models, a category of AI systems that includes LLMs. Seven months later, the Beijing Academy of AI released a similarly lengthy literature review on a related subject, with almost as many co-authors. But within a few weeks, a researcher at Google discovered that large sections of the Chinese paper had been plagiarized from a handful of international papers—perhaps, Chinese-language media speculated, because the graduate students involved in drafting the paper faced extreme pressure and were up against very short deadlines.

Americans should not be haunted by the specter of an imminent Chinese surge in LLM development. Chinese AI teams are fighting—and often failing—to keep up with the blistering speed of new research and products emerging elsewhere. When it comes to LLMs, China trails years, not months, behind its international competitors.

HEADWINDS AND HANDICAPS

Forces external to the AI industry also impede the pace of innovation in China. Because of the outsize computational demands of LLMs, the international competition over semiconductors inevitably affects AI research and development. The Chinese semiconductor industry can only produce chips several generations behind the latest cutting-edge ones, forcing many Chinese labs to rely on high-end chips developed by U.S. firms. In recent research analyzing Chinese LLMs, we found 17 models that used chips produced by the California-based firm NVIDIA; by contrast, we identified only three models built with Chinese-made chips.

Huawei’s PanGu-​​α, released in 2021, was one of the three exceptions. Trained using Huawei’s in-house Ascend processors, the model appears to have been developed with significantly less computational power than best practices would recommend. Although it is currently perfectly legal for Chinese research groups to access cutting-edge U.S. chips by renting hardware from cloud providers such as Amazon or Microsoft, Beijing must be worried that the intensifying rhetoric and restrictions around semiconductors will hobble its AI companies and researchers.

More broadly, pessimism about the overall economic and technological outlook in China may hamper domestic AI efforts. In response to a wave of regulatory scrutiny and a significant economic slowdown in the country, many Chinese startups are now opting to base their operations overseas and sell to an international market instead of selling primarily to the Chinese market. This shift has been driven by the increasing desire among Chinese entrepreneurs to gain easier access to foreign investment and to escape China’s stringent regulatory environment—while also skirting restrictions imposed on Chinese companies by the United States.

HAL, MEET BIG BROTHER

China’s thicket of restrictions on speech also pose a unique challenge to the development and deployment of LLMs. The freewheeling way in which LLMs operate—following the user’s lead to produce text on any topic, in any style—is a poor fit for China’s strict censorship rules. In a private conversation with one of us (Xiao), one Chinese CEO quipped that China’s LLMs are not even allowed to count to 10, as that would include the numbers eight and nine—a reference to the state’s sensitivity about the number 89 and any discussion of the 1989 Tiananmen Square protests.

Because the inner workings of LLMs are poorly understood—even by their creators—existing methods for putting boundaries around what they can and cannot say function more like sledgehammers than scalpels. This means that companies face a stark tradeoff between how useful the AI’s responses are and how well they avoid undesirable topics. LLM providers everywhere are still figuring out how to navigate this tradeoff, but the potentially severe ramifications of a misstep in China force companies there to choose a more conservative approach. Popular products such as the Microsoft spinout XiaoIce are prohibited from discussing politically sensitive topics such as the Tiananmen Square protests or Chinese leader Xi Jinping. Some users we spoke to even claim that XiaoIce has gotten less functional over time, perhaps as Microsoft has added additional guardrails. Journalists have likewise found that Baidu’s Ernie Bot gives canned answers to questions about Xi and refuses to respond on other politically charged topics. Given the wide range of censored opinions and subjects in China—from the health of the Chinese economy to the progress of the war in Ukraine to the definition of “democracy”—developers will struggle to make chatbots that do not cross redlines while still being able to answer most questions normally and effectively.

In addition to these political constraints on speech, Chinese AI companies are also subject to the country’s unusually detailed and demanding regulatory regime for AI. One set of rules came into force in January 2023 and applies to providers of online services that use generative AI, including LLMs. A draft of further requirements, which would apply to research and development practices in addition to AI products, was released for comment in April.

Some of the rules are straightforward, such as requiring that sensitive data must be handled according to China’s broader data governance regime. Other provisions may prove quite onerous. The January regulations, for instance, oblige providers to “dispel rumors” spread using content generated by their products, meaning that companies are on the hook if their AI tools produce information or opinions that go against the Chinese Communist Party line. The April draft would go further still, forcing LLM developers to verify the truth and accuracy not just of what the AI programs produce but also of the material used to train the programs in the first place. This requirement could be a serious headache in a field that relies on massive stores of data scraped from the Web. When carefully designed, regulation need not obstruct innovation. But so far, the CCP’s approach to regulating LLMs and other generative AI technology appears so heavy-handed that it could prove a real impediment to Chinese firms and researchers.

FEAR OF THE CHIMERA

Despite the difficulties it currently faces, Chinese AI development may yet turn a corner and establish a greater track record of success and innovation. Americans, however, have a history of overestimating the technological prowess of their competitors. During the Cold War, bloated estimates of Soviet capabilities led U.S. officials to make policy on the basis of a hypothesized “bomber gap” and then “missile gap,” both of which were later proved to be fictional. A similarly groundless sense of anxiety should not determine the course of AI regulation in the United States. After all, where social media companies resisted regulation, AI firms have already asked for it. Five years ago, Facebook founder Mark Zuckerberg warned Congress that breaking up his social media company would only strengthen Chinese counterparts. In AI, by contrast, industry leaders are proactively calling for regulation.