Problem 1: “Arms Race” Framing is Winner-Takes-All
Interpreting U.S.-China AI development as an “arms race” or a winner-takes-all competition fundamentally misunderstands the transnational nature of AI development and technological interdependence. Policy prescriptions drawn from this “race” concept will thus be ill-fit to the goals they attempt to serve. This bad fit could result in, among other undesirable outcomes, damage to AI development, missed opportunities for AI development, and mishandling of real AI risks.
Yoshua Bengio, an early pioneer of modern AI techniques, has publicly disapproved of framing AI development as a race. “We could collectively participate in a race,” he told MIT Technology Review, “but as a scientist and somebody who wants to think about the common good, I think we’re better off thinking about how to build smarter machines and make sure AI is used for the well-being of as many people as possible.”1 Possible idealism aside, his point strikes at a fundamental flaw with this arms race analogy: AI is developed by a vast community of scientists, developers, and researchers who are not isolated within their respective countries. As such, the development of AI is not siloed within Chinese or American borders, and the benefits of artificial intelligence are not exclusive to either of those nations. Public and private entities in both countries can benefit from developments of artificial intelligence in areas that have wide reach between nations and positive impacts on economic growth and public well-being (e.g., skin cancer detection). In other words, the development of artificial intelligence is not winner-takes-all. And contrary to what some commentators seem to believe (or at least constantly and singularly discuss), not every significant application of AI will be a weapon.
Graham Webster eloquently provides context on this fact through his analysis of winner-takes-all U.S.-China rhetoric. “Unlike the US and USSR, in which science and technology developed on largely independent tracks, the US and China are part of a globally intertwined ecosystem,” he explains. As a result, “companies and innovators in both countries would suffer if international research, development, and manufacturing were to shut down,” and “even if the US and China cut off trade with each other, both countries would still have to worry about security risks from components, since risks along the supply chain exist everywhere.”2 There is far more interconnection and interdependence than may otherwise be apparent in an “arms race” framing.
American firms rely heavily on Chinese manufacturing technologies (e.g., in Shenzhen),3 and that reliance is likely to grow as artificial intelligence applications made in the United States are increasingly deployed in drones, robots, and the like which may depend upon Chinese-made hardware. Trade and supply-chain links aid both countries in further developing artificial intelligence.4 China is a major market for U.S. AI hardware, and researchers from around the world—including between China and the United States—might work on similar AI problems, share data used to develop AI systems, or coauthor research papers.5 All of these factors further bolster the interconnections between the two countries’ AI sectors.
As is perhaps expected, money, too, has an impact. In 2013, Chinese investment in Silicon Valley was at $1.17 billion. By 2015, it was $11.52 billion.6 From 2012 to 2016, American firms had invested $2.6 billion in the other direction.7 While Chinese venture capitalists have invested heavily in U.S. tech companies like Uber and Airbnb,8 Tencent and Alibaba—both tech giants in China—are themselves multinational public corporations with significant ownership by international stakeholders.9 Worth noting is that both companies have extensive ties to the Communist Party of China (CCP) and the Chinese government, and are currently subject to Chinese laws mandating information-sharing with the government (e.g., via the 2017 Cybersecurity Law).10 But even this considered, there is notable economic interconnection and interdependence between AI development in the two states.
Interconnections and interdependencies between AI development in the United States and AI development in China don’t end there. China’s Tsinghua University opened an Institute for Artificial Intelligence in June 2018, for which Google’s AI Chief Jeff Dean is an advisor.11 Alibaba, another Chinese tech giant, has multiple research labs located in the United States as part of its global AI research efforts.12 China’s largest retailer has a research partnership with Stanford University’s Artificial Intelligence Lab to fund such research areas as computer vision, robotics, machine learning, forecasting, and natural language processing.13 Kai-Fu Lee, former head of Google’s operations in China, runs an AI training institution in the country that leverages the expertise of Chinese government personnel and some of North America’s “leading” computer scientists.14 And Baidu, the Chinese search company, belongs to the U.S.-based Partnership for AI, which aims to develop best practices for AI technology.15 It is worth noting potential risks associated with these kinds of relationships, including the Chinese government’s intentions to bring Western technology talent from the United States into its own country16 and previous instances of intellectual property theft. But that still doesn’t change the existence of collaborative relationships and the value garnered from at least some of them. The United States and China have many interconnections and interdependencies between their AI sectors—and so the key is in managing the risks that result therefrom, not denying the interconnectivity and interdependence in the first place.
The “AI arms race” framing implies isolated competition between two global powers, which is clearly inaccurate when it comes to the United States and China; their AI development is anything but isolated from one another. Ideally, the “openness that is so integral to American innovation should be sustained and safeguarded”17 rather than building walls between American and Chinese AI development.18 But as a result of this winner-takes-all framing, a growing emphasis on a winner-takes-all race threatens to push the two countries’ tech sectors apart, potentially damaging AI development in ways we can’t foresee. It doesn’t matter what exactly initialized this way of thinking—for instance, some would argue this is a reaction to China’s aggressive push for AI supremacy in many areas19—because this is the reality.
This bad fit could result in, among other undesirable outcomes, damage to AI development, missed opportunities for AI development, and mishandling of real AI risks.
As a result of this winner-takes-all view of AI development, mutually damaging U.S. policies towards China—like reckless trade policies or trying to hamper all collaboration on AI whatsoever—may very well hurt American AI development,20 not to mention play into Beijing’s vision of “science as a tool of national greatness and scientists as servants to the state.”21 The Trump administration’s recent talk of limiting the “export of artificial intelligence”22 is just one recent example. This winner-takes-all, race-to-the-bottom approach, which Remco Zwetsloot, Helen Toner, and Jeffrey Ding argue is guided heavily by fear and speculation,23 could further compromise the likelihood of developing sound policies that can advance mutual interests—while not lending too much advantage to Chinese AI capabilities.24
In addition to crafting hurtful policies and missing opportunities to advance mutual interests, United States policymakers, as a result of the AI arms race framing, may mishandle AI risks. An increasingly common refrain, for instance, is that any privacy regulation in the United States is going to doom AI development because Chinese competitors face no restrictions on their data collection. This argument risks exploiting individuals’ information, by which American data privacy legislation—which is desperately needed—is guided by what the Chinese government has or has not done in the same vein.25 American companies can still remain competitive in the AI sector while working under the guidance of some form of national privacy regulation.
Even generally, total disengagement with China on issues of AI ethics is not preferable either. It is well known and oft-discussed that Chinese society has different views than American society on such issues as data privacy.26 According to the executive director at Partnership for AI, “we cannot have a comprehensive and global conversation on AI development unless China has a seat at the table.”27 But with the AI arms race framing, U.S. policymakers may very well damage American AI development, miss opportunities for bolstering it, and dismiss or ignore ethical issues that need addressing under the belief of winner-takes-all AI competition.
Citations
- Will Knight, “One of the fathers of AI is worried about its future,” MIT Technology Review, November 17, 2018, source.
- Graham Webster, “The US and China aren’t in a ‘cold war,’ so stop calling it that,” MIT Technology Review, December 19, 2018, source.
- Matt Sheehan, “Does Chinese Venture Capital in Silicon Valley Threaten US Tech Advantage,” MacroPolo.org, April 26, 2018, source.
- Jack Zhang, Graham Webster, Elsa Kania, Rush Doshi, Yukon Huang, and Paul Triolo, “Should the U.S. Start a Trade War with China over Tech?” ChinaFile, June 26, 2018, source.
- Jeffrey Ding, “Deciphering China’s AI Dream,” Future of Humanity Institute, March 2018, source. Page 28.
- Matt Sheehan, “Does Chinese Venture Capital in Silicon Valley Threaten US Tech Advantage,” MacroPolo.org, April 26, 2018, source.
- According to the Wuzhen Institute, a think tank. See: The Economist, “China may match or beat America in AI,” The Economist, July 15, 2017, source.
- Cory Bennett and Bryan Bender, “How China acquires ‘the crown jewels’ of US technology,” Politico, May 22, 2018, source.
- Jeffrey Ding, “Deciphering China’s AI Dream,” Future of Humanity Institute, March 2018, source. Page 28.
- Erica Pandey, “Caged giants: Why China’s Big Tech can’t escape the Communist Party,” Axios, June 8, 2018, source.
- Synced, “Tsinghua University Launches Institute for AI; Hires Google’s Jeff Dean As Advisor,” Synced, June 28, 2018, source.
- Saheli Roy Choudhury, “Alibaba says it will invest more than $15 billion over three years in global research program,” CNBC, October 11, 2017, source; and “Laboratory,” DAMO Academy, Alibaba, accessed January 9, 2019, source.
- “Stanford Artificial Intelligence Laboratory,” Stanford University, accessed January 9, 2019, source.
- Tom Simonite, “Ex-Google Executive Opens a School for AI, with China’s Help,” WIRED, April 5, 2018, source.
- James Vincent, “US consortium for safe AI development welcomes Baidu as first Chinese member,” The Verge, October 17, 2018, source.
- Alex Keown, “China’s ‘Thousand Scientists Plan’ Recruits Western Scientists and Researchers,” BioSpace, November 19, 2018, source.
- Jack Zhang, Graham Webster, Elsa Kania, Rush Doshi, Yukon Huang, and Paul Triolo, “Should the U.S. Start a Trade War with China over Tech?” ChinaFile, June 26, 2018, source.
- Anja Manuel, “Chinese Tech Isn’t the Enemy,” The Atlantic, August 1, 2018, source.
- Gregory C. Allen, “China’s Artificial Intelligence Strategy Poses a Credible Threat to U.S. Tech Leadership,” Council on Foreign Relations, December 4, 2017, source.
- It’s worth noting this winner-takes-all view of U.S.-China relations is a problem in general. President Obama attempted to move away from this view during his presidency, but it has returned under the presidency of Donald Trump. See: Robert G. Patman and Timothy G. Ferner, “Paul Kennedy’s Conception of Great Power Rivalry and US-China Relations in the Obama Era” in The Changing East Asian Security Landscape, Wiesbaden: Springer Vieweg (2017), edited by Stefan Fröhlich and Howard Loewen, source; and Rachel Esplin Odell, “Chinese Regime Insecurity, Domestic Authoritarianism, and Foreign Policy” in “AI, China, Russia, and the Global Order: Technological, Political, Global, and Creative Perspectives,” Strategic Multilayer Assessment Publication, December 2018, source.
- A longer, pulled quote on the issue: “The United States may feel it’s only playing defense in a global cold war over tech. In reality, these policies play into Beijing’s preferred vision of the world. China sees science as a tool of national greatness and scientists as servants to the state. This parochial vision discounts the individual agency and ethical obligations of scientists and runs contrary to the cosmopolitan ideal of science. The United States must uphold those ideals, not create new boundaries.” See: Yangyang Cheng, “Don’t Close the Door on Chinese Scientists Like Me,” Foreign Policy, June 4, 2018, source.
- Tony Romm, “Trump administration proposal could target exports of the tech behind Siri, self-driving cars and supercomputers,” The Washington Post, November 19, 2018, source.
- Remco Zwetsloot, Helen Toner, and Jeffrey Ding, “Beyond the AI Arms Race,” Foreign Affairs, November 26, 2018, source.
- As Lorand Laskai and Samm Sacks have written, “Any attempt to separate the two technology sectors by force would prove counterproductive at best and devastating at worst. This simultaneously competitive and interdependent relationship warrants a completely different strategy—one that exploits the benefits of collaboration while strengthening the United States’ ability to compete.” See: Lorand Laskai and Samm Sacks, “The Right Way to Protect America’s Innovation Advantage,” Foreign Affairs, October 23, 2018, source.
- Graham Webster and Scarlet Kim, “The Data Arms Race Is No Excuse for Abandoning Privacy,” Foreign Policy, August 14, 2018, source.
- This is underscored by, for instance, the fact that Chinese and American businesspeople alike consistently point out, in recent years, a lack of data privacy protections in China: Greg Williams, “Why China will win the global race for complete AI dominance,” WIRED, April 16, 2018, source; and Natasha Lomas, “Zuckerberg urges privacy carve outs to compete with China,” TechCrunch, April 10, 2018, source. But some American analysts’ misconceptions—or perhaps generalizations—about views and policies in China around surveillance and data privacy are changing, as aided by some recent work. See: Samm Sacks, “New China Data Privacy Standard Looks More Far-Reaching than GDPR,” Center for Strategic & International Studies, January 29, 2018, source; Samm Sacks, “China’s Emerging Data Privacy System and GDPR,” Center for Strategic & International Studies, March 9, 2018, source; Jeffrey Ding, “Deciphering China’s AI Dream,” Future of Humanity Institute, March 2018, source; and Samm Sacks and Lorand Laskai, “China’s Privacy Conundrum,” Slate, February 7, 2019, source. Also see: Evelyn Cheng, “Data privacy issues may be capturing more attention in China,” CNBC, December 4, 2018, source.
- James Vincent, “US consortium for safe AI development welcomes Baidu as first Chinese member,” The Verge, October 17, 2018, source.