The CSS Blog Network

Now I Know My ABCs: US-China Policy on AI, Big Data, and Cloud Computing

Image courtesy of M Woods

This publication was originally published by the East-West Center in September 2019.

Summary

Artificial Intelligence (AI), Big Data, and Cloud Computing (ABC) have generated unprecedented opportunities and challenges for economic competitiveness, national security, and law and order, as well as the future of work. ABC policies and practices have become contentious issues in U.S.-China bilateral relations. Pundits see a U.S.-China AI race and are already debating which country will win. Kaifu Lee, the CEO of Sinovation Ventures, believes that China will exceed the United States in AI in about five years.1 Others argue that China will never catch up.2 This essay focuses on two issues: the comparative ABC strengths of the United States and China in data and research and development (R&D); and the emerging ABC policies and practices in the two nations. Empirical analysis suggests that the United States and China lead in different areas. Compared to China’s top-down, whole-of-government, national- strategy approach, the U.S. ABC policy has been less articulated but is evolving.

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Have Strategists Drunk the “AI Race” Kool-Aid?

Image courtesy of Ecole polytechnique/Flickr. (CC BY-SA 2.0)

This article was originally published by War on the Rocks on 4 June 2019.

Has global strategic competition become a race for dominance in artificial intelligence (AI) between the United States and China? Versions of this claim have become something of an axiom, offered by officialdom and the analytical community alike. That AI will be the primary axis of future strategic competition is contestable, however. Moreover, the notion of an AI race in and of itself will generate policy risk. Making policy based on those assumptions could lead to narrowing options, not only in the realm of competition between states but regarding human affairs in general.

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A Politically Neutral Hub for AI Research

Image courtesy of Geralt/Pixabay

This article was originally published by the ETH Zukunftsblog on 24 May 2019. 

The growing politicisation of AI harbours risks. Sophie-Charlotte Fischer and Andreas Wenger propose a hub for AI research in Switzerland committed to the responsible development of the new technologies.

The surge of progress in Artificial Intelligence (AI) over the last few years has been driven primarily by economic market forces and the manifold commercial applications. Large global technology companies, particularly in the US and China, lead the field in AI. Yet this concentration of AI resources in a few private corporations is increasingly undercutting the competitiveness of public research institutions and smaller companies. Such oligopolistic market dynamics threaten to exacerbate existing economic and social inequalities.

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AI and Autonomous Systems Are Urgent Priorities for Today’s Defence Force

Image courtesy of Daniel Wetzel/DVIDS

This article was originally published in the Strategist by the Australian Strategic Policy Institute (ASPI) on 29 April 2019.

The 2016 defence white paper and the decades-long integrated investment program will deliver a future force that includes 72 joint strike fighters, several hundred infantry fighting vehicles, nine new frigates and 12 new submarines. F-35 deliveries have started but the ‘future’ frigate and submarine programs were well named: the Hunter-class frigates will turn up, all going well, between 2028 and the early 2040s, and the first Attack-class submarine is scheduled to enter service in 2035, with the 12th in the mid-2050s.

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Preparing for “NATO-mation”: The Atlantic Alliance toward the Age of Artificial Intelligence

Image courtesy of U.S. Department of Energy/Flickr.

This article was originally published by the NATO Defense College (NDC) in February 2019.

The unprecedented pace of technological change brought about by the fourth Industrial Revolution offers enormous opportunities but also entails some risks. This is evident when looking at discussions about artificial intelligence (AI), machine learning (ML) and big data (BD). Many analysts, scholars and policymakers are in fact worried that, beside efficiency and new economic opportunities, these technologies may also promote international instability: for instance, by leading to a swift redistribution of wealth around the world; a rapid diffusion of military capabilities or by heightening the risks of military escalation and conflict. Such concerns are understandable. Throughout history, technological change has at times exerted similar effects. Additionally, human beings seem to have an innate fear that autonomous machines might, at some point, revolt and threaten humanity – as illustrated in popular culture, from Hebrew tradition’s Golem to Mary Shelley’s Frankenstein, from Karel Čapek’s Robot to Isaac Asimov’s I, Robot and the movie Terminator.

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