What is artificial intelligence bringing to international trade?

Artificial intelligence (AI) straddles the separate worlds of products and ideas. In the world of products, it is used to create and improve goods and services. In the world of ideas, it is a new method of research and development, a re-invention of invention. This distinction between products and ideas is important in light of increasing evidence that the international movement of ideas likely will be even more pivotal for societal success than the international movement of goods.

AI and Covid vaccines

AI relies on data

Regulatory approval for vaccines was not possible without large-scale clinical trials, which relied on the availability of data. In the US, the horrendous spread of Covid generated abundant data for clinical trials. In China, the initially effective pandemic response made Covid too rare for clinical trials, forcing China to rely on data collected abroad in countries such as Brazil. We rightly worry about data privacy, especially when our personal information is in the hands of foreign entities. However, we must remember that data privacy regulation and data localization rules, while essential, come at a cost. In the case of Covid, the cost is our health.

AI and trade need trust

China’s inactivated-virus vaccines are rarely used in Western countries and Western mRNA vaccines are not approved in China. Despite the clear superiority of mRNA vaccines, according to some estimates, 75% of Chinese citizens do not trust them. Distrust has many causes, but in this case the consequences are clear. Distrust of foreign vaccines, and foreign AI-enabled products more generally, severely limits international trade.

Managing AI's risks

Big AI superstars such as Moderna, Google, and Tencent are almost all located either in the US or China. In the future, the rest of the world will pay the US and China hefty royalties for AI-based intellectual property. Restated, the US and China will reap the largest financial benefits from AI at the expense of all other countries. How this exacerbates global inequality will depend on how we manage the ownership of data, intellectual property regimes, and competition policy.

Because AI straddles the worlds of ideas and goods, it is exceedingly difficult for the consumer to know which goods and services use AI. You might be surprised to know, for example, that Google search made minimal use of AI until 2019. However, my research shows that we can track a large swath of AI-related international trade by tracking the digital services on our phones. Each day we use AI to sift through the news, check out friends’ posts, shop online, search the internet, transfer money, and more. For many years now, my colleague Ruiqi Sun and I have been tracking the international use of mobile apps. This international trade in digital services is a trillion-dollar market and so represents a substantial chunk of all international trade.

AI's costs: The reorganization of global value chains

AI comes with significant costs. We can expect a loss of privacy, reduced competition that leads to rising inequality both within and between countries, and an orchestrated degradation of trust in our domestic and international institutions. This will damage our ability to deliver sustainable and inclusive growth to citizens of the world. In my view, it is the degradation of inclusive institutions such as democracy that will ultimately do the most harm. This view stems from years of research indicating that while the proximate source of the wealth of nations is innovation, the ultimate source of wealth is the effectiveness of national and international institutions that support innovation and equitably distribute its benefits.

We should not expect a major AI-induced change in the location of jobs or the connectedness of jobs within global value chains because AI displaces tasks rather than jobs and AI adoption involves slow organizational change. AI-induced re-shoring and loss of developing-economy jobs are storm clouds on a distant horizon.

A proposal for international regulation of AI

The European Union’s General Data Protection Regulation (GDPR) is the most ambitious and studied example of internationally harmonized AI regulation. We now know that GDPR reduces the profits of corporations because they cannot harvest private data without consent. This is a welcome development. On the downside, GDPR has also reduced the variety of available apps, the download of apps, and the consumer benefits of using these apps. More speculatively, it may have contributed to the stunting of European tech giants. As a result, there have been calls to replace GDPR. Despite the obvious need to protect privacy, the history of GDPR illustrates that such policies must be tailored to reduce their costs.

In discussing AI regulation, we often work with high-level statements that apply to all AI. Yet AI is a collection of diverse algorithms with diverse use cases. To successfully harmonize regulation, we must concentrate on individual use cases such as autonomous vehicles or robots. This is how most harmonized regulation will emerge. A working model is 3GPP, the organization which sets mobile telecommunications standards for 5G. While such organizations are the best way forward, they are not without problems. For one, corporate rather than public interest drives their regulation. For another, governments, particularly China, are taking an increasingly active role in supporting standards that give advantage to their own firms.

Standards organizations are the future of international AI harmonization, but civil society must be on guard for threats to equality, inclusiveness, social cohesion, and democracy. Guard duty begins by better informing ourselves of the issues I have raised here. 

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The Hinrich Foundation's Sustainable Trade Index 2022, launched on November 8, measures the relative capacity of 30 key economies worldwide to achieve sustainable growth through global trade. Among other indicators, the index measures and ranks economies on the extent of their technological innovation and tech infrastructure, both of which influence AI. Innovation was measured largely by R&D while infrastructure by internet quality. Asian economies topped the rankings for these indicators, including South Korea, Singapore, Taiwan, Hong Kong, and Japan.

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