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Reframing AI Competition & Conclusion

We are in an era of great power competition, and the United States and China are undoubtedly in competition with respect to artificial intelligence. AI, which is a catch-all term for a number of technologies, will impact state power—primarily via economic growth and military capability—and allow global norm-setting on AI and technology writ large in fashions that impact the future world order. In short, artificial intelligence is a vital element of U.S.-China great power competition. But the winner-takes-all arms race view of this competition is wrong and dangerous for American policymaking, which is why it must be reframed.

Understanding Interconnection and Interdependence

First, U.S. policymakers need to understand the interdependence and interconnection of AI development between the United States and China. Competition is a fine way to put it, but an arms race sounds as if AI development is siloed within each country. This leads to impractical statements about export controls on artificial intelligence writ large—which anyone aware of AI research’s open source nature would certainly dismiss as impractical.

Some experts have agreed on the value of paying attention to China potentially exploiting U.S. policy gaps to undermine American technological advantages, which the export controls in some sense address. But others point out that top universities and businesses alike are concerned about “possibly throttling a vital source of research” due to proposed blocks on industry collaboration.1 And it isn’t just about research collaboration. Important funding and resources for American AI research could also be blocked as a result. The Center for Data Innovation, for instance, writes that export restrictions on AI technologies could “substantially reduce” opportunities for American firms to sell their AI products and services, thereby harming U.S. AI competitiveness.2 Jack Clark, head of policy at OpenAI, holds that “the number of cases where exports can be sufficiently controlled are very, very, very small, and the chance of making an error is quite large.” Further, MIT’s R. David Edelman notes, trying to distinguish in export control policies between what is military versus civilian use of AI “may be impossible.”3 In short, overlooking U.S.-China interconnection and interdependence in AI development may very well lead to policies that try to sever connections between AI sectors and thereby harm AI development in the process.

Rather than try to blindly and broadly apply export controls to AI under the myth of winner-takes-all AI development, American policymakers should focus on ways in which China is actually aided in a winner-takes-all fashion by American ideas or resources—like through its theft of American intellectual property.4

In September 2015, President Obama and President Xi announced at a White House press conference: “We’ve agreed that neither the U.S. or the Chinese government will conduct or knowingly support cyber-enabled theft of intellectual property, including trade secrets or other confidential business information for commercial advantage.”5 This seemed to work initially, and Chinese hacking of American companies notably dropped for a brief period, though this didn’t directly translate to increased U.S.-Chinese cooperation on other cyberspace issues.6 (For evidence of this since 2015, see the aforementioned work my colleague and I have done to document China’s proposals for cyber codes of conduct in the UN and other international bodies, which the United States and its allies have resisted due to fundamental disagreements over issues of internet governance and so-called cyber sovereignty.)

American policymakers should focus on ways in which China is actually aided in a winner-takes-all fashion by American ideas or resources—like through its theft of American intellectual property.

It’s clear, however, that this no-IP-theft agreement has fallen apart since President Trump took office,7 despite initial proclamations that the Trump administration would stick with the agreement.8 The volume of hacking in this vein is back up. By the estimation of one independent commission, China now accounts for 50 to 80 percent of the annual $300 billion in American economic losses from thefts of intellectual property.9 A March 2018 report from the Office of the U.S. Trade Representative reached similar conclusions: “Beijing’s cyber espionage against U.S. companies persists and continues to evolve,” as “Chinese state-sponsored cyber operators continue to support Beijing’s strategic development goals, including its S&T advancement, military modernization, and economic development.”10 Without getting too much into the nuance of the Obama-Xi agreement11 and the changes in Chinese hacking that resulted therefrom, the point is that American AI development is necessarily harmed by China’s industrial espionage, both online and offline.

The same goes for the potential security risks of Chinese investments in American AI companies; a January 2017 report to the president warned, for instance, about China’s challenge to American leadership in semiconductors—which make the microchips in many advanced technologies—via investment in U.S. firms.12 But between these problems and broad, sweeping plans for limiting industry collaboration on AI, the U.S. government cannot effectively combat China’s technological rise without recognition of the interconnection and interdependence of American and Chinese AI development.

Addressing the Many Technologies at Hand

Second, U.S. policymakers cannot approach artificial intelligence as if it’s one technology. Doing so treats all AI implementations as the same, which is wrong—and leads to narrow thinking about how to bolster AI development. To see this in practice, look no further than U.S. policymakers’ intense focus on AI’s military applications at the cost of neglecting its non-military ones (perhaps another result of calling it an arms race).

Particularly for national security professionals who speak vaguely (and widely speculatively) of a world with automated fighting and a changed character of battle and war, military applications of AI—such as autonomous surveillance drones or intelligently automated command and control systems—are a stereotypical answer for how AI will impact state power. This answer is not wrong. China, as already discussed, well recognizes this fact, as does the United States and other countries like Russia13 who have invested in defense-focused AI applications.

But many other non-military applications of AI are particularly important for state power in the ways they could boost the economy, and they too must be a part of policymakers’ thinking on the technologies captured in the term artificial intelligence. Healthcare, for instance, is a particularly promising area for AI’s impact on economic growth. Cancer detection, eye health, coma treatments, and depression prediction are just some of the varied ways in which AI implementations are already revolutionizing medicine around the world.14 Disease prediction in particular has received much research attention, insofar as AI systems may combat such issues as doctors’ decision fatigue.

This is not to overstate the ability of modern machine learning algorithms to identify cancers or predict epidemics; many legal and ethical issues plague AI in healthcare (e.g., data privacy, AI bias) and other challenges such as data labeling, data sampling, and clinical integration will put additional limits on how, and how quickly, AI implementations will impact the American and global healthcare systems.15 But this is to say that the U.S. government should not only focus on military applications of AI. This entirely ignores potential AI application areas with promise to improve quality of life and greatly boost American economic power in the process.

Moreover, in either case, AI is still not one technology: Facial recognition systems deployed in military drones are different than natural language processors used to spy on phone calls, and image recognition algorithms to detect brain tumors are different than intelligent systems that manage hospital supply chains. Yet all could fall under the banner of AI, and all can have important impacts on state power via the military and the economy.

U.S. policymakers must therefore prioritize investments in AI, and policies towards AI development, that attempt to maximize state power in both military and economic dimensions—all while understanding that Congress and other bodies must address the legal and ethical issues raised by the various forms these AI implementations may take.

Bolstering American AI Capabilities

Without a doubt, the U.S. government needs to invest more in developing artificial intelligence within its borders. Congress must work to advance standard development for safe artificial intelligence16 and explore regulating certain public uses of AI that disproportionately harm minorities and other already disadvantaged groups, such as racially biased facial recognition in urban centers.17 Both of these policy actions would help integrate AI into American society in ways better aligned with democratic principles. This would further help to promote global norms around democratic uses of AI.18

More broadly, the United States needs a whole-of-government approach to artificial intelligence that its Chinese counterparts have already begun to execute. The United States must focus on deciphering the investments and policies most important to maximizing military and economic gains, while still working carefully to promote and ensure democratic uses of AI domestically. For instance, Congress should work to support collaborative health research related to AI while still working to legally protect the privacy of patient information. The National Institute of Standards and Technology (NIST) should work with industry trade organizations like the Institute of Electrical and Electronics Engineers to help set standards for ethical uses of AI facial recognition, while the American defense apparatus should do similar, parallel work in the military vein. A multi-pronged and multi-stakeholder approach is needed for AI development. This is especially true given China’s multi-pronged and multi-stakeholder investment in AI.

The United States needs a whole-of-government approach to artificial intelligence that its Chinese counterparts have already begun to execute.

Chinese business and government entities have poured billions of dollars (USD) into artificial intelligence development over the last decade.19 The Chinese government has also released a variety of plans and held a number of dialogues on further developing AI, which spans the founding of AI-specific educational institutes, creating AI majors at universities, and communicating and coordinating AI research among research institutes, universities, enterprises, and military industry.20 It remains to be seen how well these plans will be executed upon,21 but their construction nonetheless reflects government effort to bolster AI development within Chinese borders—clearly, acknowledging AI’s many forms.

In sum, the Chinese government’s actions are “a clear indication of governmental commitment to this agenda at the highest levels,”22 while the United States, meanwhile, has yet to implement a cohesive, national AI strategy.23 The U.S. Treasury Secretary said back in 2017 that AI worker displacement was “not even on [their] radar screen.”24 (This is only further evidence of U.S. policymakers focusing, at the highest levels, too much on AI’s military applications and not enough on its potential applications in, say, healthcare.) While the United States has strong advantages in developing various forms of artificial intelligence—such as a talented workforce25 and highly influential research coming from its scholars and practitioners26—the country still needs whole-of-government investment in developing artificial intelligence. The likes of a Defense Innovation Board for ethics of AI in war,27 a Joint Artificial Intelligence Center,28 and a new Congressional AI commission,29 while valuable steps, are not enough.30

U.S. federal agencies should all be strategizing about the research, development, and implementation of AI in their organizations, and this should be happening with top-down direction from the White House. Congress should simultaneously be exploring regulatory data privacy frameworks that seek to maintain AI competitiveness in the military, government, and industry while still protecting consumers’ and citizens’ information. But these lofty goals must start with a few tangible policy steps.

  • Stop with the AI arms race rhetoric. American policymakers must acknowledge that AI development is not winner-takes-all and that AI is not a single technology—and then ditch the arms race framing. Journalists, too, should take greater care in reporting on AI development in ways that don’t imply a winner-takes-all competition. Alongside this, the national security establishment—spanning think tanks, academia, and high-level U.S. policy offices—should, alongside writing and strategizing about AI’s impact on military capability, take care to put similar focus on AI’s impact on economic power. The U.S. government in particular should explicitly include the influence of AI on economic power in national security and defense strategies, paying far more attention to non-military AI applications.
  • Develop a national AI strategy. The White House needs to develop a cohesive, national AI strategy document highlighting the importance of AI for bolstering economic and military power, as well as the importance of working to promote democratic uses of AI domestically and around the world. From China to France, other countries have done so—yet the United States has not, despite vague term-dropping of “artificial intelligence” in such documents as the 2017 National Security Strategy31 or the 2019 National Intelligence Strategy.32 Individual agency strategies or reports on artificial intelligence, such as that from the Director of National Intelligence,33 are not enough either, and the February 11 Executive Order on maintaining American leadership in AI34 is still not a cohesive, national strategy that compares to what China has developed. In spite of the Trump administration’s unprecedented vacancies in the White House Office of Science & Technology Policy,35 the White House should also hire, and consult with, artificial intelligence experts in the design of this strategy.
  • Bolster diplomatic cyber capacity. Especially after the closing of the Office of Coordinator for Cyber Issues at the U.S. State Department—amid broader State Department cutbacks and the retraction of American diplomatic arms—the U.S. federal government needs to devote more diplomatic capacity36 to fighting the model of digital authoritarianism that China currently champions. This involves such policy actions as helping smaller countries build diplomatic cyber capacity; building international norms that champion the value of a global and open internet and ethical uses of ethical AI; and emphasizing the value of democratic uses of AI for economic growth. Major agreements and dialogues around cyberspace and AI are occurring in international forums, yet the United States isn’t nearly active enough in delivering a clear, cohesive message that opposes digital authoritarianism. The State Department has announced the creation of a new cybersecurity bureau,37 but this should be further supplemented by greater diplomatic focus on AI—on formal agreements, standard-setting, and global norms and practices around AI’s use and regulation in society.
  • Tighten controls on selling AI surveillance products to dictators. American policymakers must also evaluate how some of its own private companies slip through the cracks of existing export controls and sell surveillance technology to authoritarians like Saudi Arabia.38 Such practices make the United States look hypocritical and serve to further justify China’s narrative around undemocratic uses of AI for social control and “national security.” From the 2013 multilateral arms-control Wassenaar Arrangement, for instance, the United States has not implemented the “IP network communications surveillance systems” control, unlike the entire E.U. bloc and most other Wassenaar participants.
  • Address Chinese intellectual property theft. While many research collaborations between American and Chinese AI sectors undoubtedly hold benefits for both countries, the United States is losing massive technological advantages in a number of sectors due to China’s widespread IP theft; and this certainly includes AI. It’s likely that the widely publicized 2015 U.S. indictments of Chinese hackers influenced the subsequent Obama-Xi agreement, so the Department of Justice should make it a clear priority today to indict Chinese hackers for stealing American IP. Among other policy changes, this would be helped by bolstering incentives for the FBI to prosecute cybercrime cases, increasing interagency cooperation, and bolstering diplomatic cyber capacity.39 Borrowing from Lorand Laskai and Adam Segal at the Council on Foreign Relations, the U.S. government should also combine indictments for Chinese IP theft with targeted sanctions against the entities from which thefts occur, and work with potential American targets to strengthen their cybersecurity.40
  • Enact national data privacy legislation. The United States must develop a stance on data governance that contrasts with China’s model of pervasive government surveillance, while still upholding democratic norms around consumer protection. To think that any and all privacy laws will massively hinder American AI development is not only quite speculative, but follows a dangerous narrative whereby ethical considerations around AI should be cast aside in the service of trying to bolster national AI power. Not only does this narrative seek to serve major American technology companies which desire minimal regulation,41 but it also ignores the importance of the United States and its allies upholding democratic norms around AI—which includes addressing such issues as AI bias and data privacy—in order to promote a less authoritarian global order.

While the United States needs to worry about China’s AI ambitions, an arms race framing is not the right approach. Before any true policy changes can be made to aid the United States in this great power competition with China, American policymakers at the highest levels—as well as American academics, journalists, and national security analysts writ large—must ditch the AI arms race metaphor.

Citations
  1. Kaveh Waddell, “Trump administration’s proposed export controls could hinder tech research,” Axios, November 28, 2018, source.
  2. Daniel Castro and Joshua New, “Memorandum to Matthew S. Borman, Deputy Assistant Secretary for Export Administration: Review of controls for certain emerging technologies,” Center for Data Innovation, December 6, 2018, source.
  3. Cade Metz, “Curbs on A.I. Exports? Silicon Valley Fears Losing Its Edge,” The New York Times, January 1, 2019, source.
  4. Alyza Sebenius and Nico Grant, “China Violating Cyber Agreement With U.S., NSA Official Says,” Bloomberg, November 8, 2018, source; and Lorand Laskai and Adam Segal, “A New Old Threat: Countering the Return of Chinese Industrial Cyber Espionage,” Council on Foreign Relations, December 6, 2018, source.
  5. White House Office of the Press Secretary, “Remarks by President Obama and President Xi of the People’s Republic of China in Joint Press Conference,” White House, September 25, 2018, source.
  6. Adam Segal, “The U.S.-China Cyber Espionage Deal One Year Later,” Council on Foreign Relations, September 28, 2016, source.
  7. Alyza Sebenius and Nico Grant, “China Violating Cyber Agreement With U.S., NSA Official Says,” Bloomberg, November 8, 2018, source; and Lorand Laskai and Adam Segal, “A New Old Threat: Countering the Return of Chinese Industrial Cyber Espionage,” Council on Foreign Relations, December 6, 2018, source.
  8. Cory Bennett, “Why Trump is sticking with Obama’s China hacking deal,” Politico, November 8, 2017, source.
  9. Adam Segal, “The U.S.-China Cyber Espionage Deal One Year Later,” Council on Foreign Relations, September 28, 2016, source.
  10. Office of the United States Trade Representative, “Findings of the Investigation into China’s Acts, Policies, and Practices Related to Technology Transfer, Intellectual Property, and Innovation Under Section 301 of the Trade Act of 1974,” Executive Office of the President, March 22, 2018, source. Page 168.
  11. Stanford University’s Herb Lin, for instance, has good discussion on just how intellectual property theft and espionage were defined: Herb Lin, “What the National Counterintelligence and Security Center Really Said About Chinese Economic Espionage,” Lawfare, July 31, 2018, source.
  12. President’s Council of Advisors on Science and Technology, “Ensuring Long-Term U.S. Leadership in Semiconductors,” Executive Office of the President, January 2017, source. Relatedly, also see: Paul Triolo and Graham Webster, “China’s Efforts to Build the Semiconductors at AI’s Core,” New America, December 7, 2018, source.
  13. Vladimir Putin famously said in 2017 that “whoever leads in AI will rule the world,” and in that vein, the country is indeed taking steps to invest in AI’s military applications. See: Russia Today, “‘Whoever leads in AI will rule the world’: Putin to Russian children on Knowledge Day,” Russia Today, September 1, 2017, source; and Alina Polyakova, “Weapons of the weak: Russia and AI-driven asymmetric warfare,” Brookings Institution, November 15, 2018, source.
  14. Alex Gray, “7 amazing ways artificial intelligence is used in healthcare,” World Economic Forum, September 20, 2018, source.
  15. Choong Ho Lee and Hyung-Jin Yoon, “Medical big data: promise and challenges,” Kidney Research and Clinical Practice (Vol. 36: Issue 1), March 2017, 3-11, source.
  16. Elsa B. Kania, “Challenges of technological innovation and competition in the new year,” The Hill, December 29, 2018, source.
  17. Among other arguments, findings, and recommendations: Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner, “Machine Bias,” ProPublica, May 23, 2016, source; Justin Sherman, “AI and machine learning bias has dangerous implications,” Opensource.com, January 11, 2018, source; Karl M. Manheim and Lyric Kaplan, “Artificial Intelligence: Risks to Privacy and Democracy,” Social Science Research Network, October 26, 2018, source; AI Now Institute, “AI Now Report 2018,” AI Now Institute, 2018, source; Justin Sherman, “Need a resolution? How about ‘Guard your online presence,’” Richmond Times-Dispatch, December 31, 2018, source; Ross Barkan, “New York should regulate law enforcement use of facial recognition technology,” City & State NY, January 7, 2019, source; and Sophie Haigney, “Not All Surveillance is Created Equal,” Pacific Standard, January 7, 2019, source.
  18. For discussion of some issues in this vein, see: Steven Feldstein, “The Road to Digital Unfreedom: How Artificial Intelligence is Reshaping Repression,” Journal of Democracy (Vol. 30: Issue 1), January 2019, 40-52, source.
  19. Vikram Barhat, “China is determined to steal A.I. crown from US and nothing, not even a trade war, will stop it,” CNBC, May 4, 2018, source; Alison DeNisco Rayome, “Chinese AI startups raised $5B in VC funding last year, outpacing the US,” TechRepublic, August 27, 2018, source; and Jeffrey Ding, “Deciphering China’s AI Dream,” Future of Humanity Institute, March 2018, source. Pages 7, 16, and 17.
  20. Graham Webster, Rogier Creemers, Paul Triolo, and Elsa Kania, “China’s Plan to ‘Lead’ in AI: Purpose, Prospects, and Problems,” New America, August 1, 2017, source; Elsa Kania and Rogier Creemers, “Xi Jinping Calls for ‘Healthy Development’ of AI (Translation),” New America, November 5, 2018, source; Cameron Hickert and Jeffrey Ding, “Read What Top Chinese Officials Are Hearing About AI Competition and Policy,” New America, November 29, 2018, source; and Jeffrey Ding, Paul Triolo, and Samm Sacks, “Chinese Interests Take a Big Seat at the AI Governance Table,” New America June 20, 2018, source.
  21. Graham Webster, Rogier Creemers, Paul Triolo, and Elsa Kania, “China’s Plan to ‘Lead’ in AI: Purpose, Prospects, and Problems,” New America, August 1, 2017, source.
  22. Gregory C. Allen and Elsa B. Kania, “China is Using America’s Own Plan to Dominate the Future of Artificial Intelligence,” Foreign Policy, September 8, 2017, source.
  23. Joshua New, “Why It’s Time for the United States to Develop a National AI Strategy,” Center for Data Innovation, December 4, 2018, source.
  24. Shannon Vavra, “Mnuchin: Losing human jobs to AI ‘not even on our radar screen,’” Axios, March 24, 2017, source.
  25. Iris Deng, “China’s AI industry gets the most funding, but lags the US in key talent, says Tsinghua,” South China Morning Post, July 17, 2018, source.
  26. Dominic Barton, Jonathan Woetzel, Jeongmin Seong, and Qinzheng Tian, “Artificial Intelligence: Implications for China,” McKinsey Global Institute, April 2017, source. Page 5.
  27. Aaron Boyd, “Defense Innovation Board to Explore the Ethics of AI in War,” Nextgov, October 11, 2018, source.
  28. Sydney J. Freedberg, “Joint Artificial Intelligence Center Created Under DoD CIO,” Breaking Defense, June 29, 2018, source.
  29. Paul Scharre and Michael C. Horowitz, “Congress Can Help the United States Lead in Artificial Intelligence,” Foreign Policy, December 10, 2018, source.
  30. For examples of other U.S. steps to bolster AI development, see: “AI Policy – United States,” Future of Life Institute, accessed on January 10, 2019, source.
  31. White House, “National Security Strategy of the United States of America,” White House, December 2017, source. Pages 20 and 34.
  32. Office of the Director of National Intelligence, “National Intelligence Strategy of the United States of America,” Office of the Director of National Intelligence, 2019, source.
  33. Public-Private Analytic Exchange Program, “AI: Using Standards to Mitigate Risks,” U.S. Department of Homeland Security, 2018, source; and Office of the Director of National Intelligence, “The AIM Initiative: A Strategy for Augmenting Intelligence Using Machines,” Office of the Director of National Intelligence, 2018, source.
  34. White House, Executive Order on Maintaining American Leadership in Artificial Intelligence, White House, February 11, 2019, source.
  35. Ben Guarino, “Trump desperately needs a science adviser, experts say. He just doubled the record for time without one,” The Washington Post, July 27, 2018, source.
  36. Justin Sherman, “To Preserve a Global and Open Internet, We Need to Invest in Cyber Diplomacy,” New America, December 11, 2018, source; and Justin Sherman and Robert Morgus, “Four Opportunities for State’s New Cyber Bureau,” New America, February 11, 2019, source.
  37. Robbie Gramer and Elias Groll, “Can State’s New Cyber Bureau Hack It?” Foreign Policy, January 18, 2019, source.
  38. Robert Morgus and Justin Sherman, “How U.S. surveillance technology is propping up authoritarian regimes,” The Washington Post, January 17, 2019, source.
  39. Mieke Eoyang, Allison Peters, Ishan Mehta, and Brandon Gaskew, “To Catch a Hacker: Toward a comprehensive strategy to identify, pursue, and punish malicious cyber actors,” ThirdWay, October 29, 2018, source.
  40. Lorand Laskai and Adam Segal, “A New Old Threat: Countering the Return of Chinese Industrial Cyber Espionage,” Council on Foreign Relations, December 6, 2018, source.
  41. Graham Webster and Scarlet Kim, “The Data Arms Race Is No Excuse for Abandoning Privacy,” Foreign Policy, August 14, 2018, source.
Reframing AI Competition & Conclusion

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