AI and trade: the view from Europe

The European Parliament has published two briefings and an in-depth analysis on “Data flows, artificial intelligence and international trade: impacts and prospects for the value chains of the future”. In Part 1, we summarize the EU’s briefing on the socio-economic effects: a fall in trade of manufactured products and unprecedent global competition (and outsourcing) in services.

Socio-economic effects of digital trade and AI on global supply chains and EU trade

The first briefing suggests that digital trade is likely “to vastly increase trade between advanced and emerging economies”, raising “important issues for domestic policies and trade policy”. It views artificial intelligence (AI) as a “general-purpose technology” with the potential “to transform digital trade by greatly reducing geographical barriers”. It finds that “digital technologies have fundamentally changed the behaviour of consumers” by “increasing the transparency over information about products that are available to consumers” and “monetising data in digital services” through personalised products and services. It also notes that blockchain technology has reduced reliance on intermediaries.

digital technologies have fundamentally changed the behaviour of consumers

The briefing warns that “trust is a fundamental factor for the growth and success of online trade”. (The EU, and other governmental and inter-governmental bodies, have repeatedly raised trust as a key challenge for the use of AI; see, for example, the European Commission’s White Paper on Artificial Intelligence: a European approach to excellence and trust.) It notes the EU safeguards within the General Data Protection Regulation and the EU’s promotion of data portability in the Free Flow of Data Regulation and The Digital Content Directive. It further warns of market concentration “through data-driven economies of scope and the presence of strong network effects”, naming familiar Big Tech companies.

robotics and AI may actually reduce trade in manufactured goods, while vastly increasing trade in services

The briefing predicts that AI may “reduce trade in manufactured goods”, further reducing employment in manufacturing. The trade implications will be affected by AI’s impact on transportation and transaction costs and on the labour-intensity of production. If the latter falls, manufacturing may be localised, reducing trade, particularly if transport costs remain significant. This effect could be increased by additive manufacturing (aka 3D printing), although its use is “still very limited”.

By contrast, digital transformation “is making more and more services digitally deliverable”. Services will be relatively labour-intensive, driving companies to “delocalise production from advanced countries to countries with relatively cheap skilled labour” and encouraging more companies to use “telemigrants” (foreign-based online service workers) – a trend accelerated by COVID-19. The briefing predicts:

Soon it will be to South Asia (mainly India) and other countries with good education systems, that services jobs from advanced economies will migrate, and on a much bigger scale than what has already occurred.

European workers in services that were “hitherto non-tradable (or little tradable)” and have been “sheltered” to date from international competition will face outsourcing. The briefing does not predict the impact on employment, but notes that globalisation has, so far, changed the composition of EU jobs, not the number of jobs, and increased leisure time.

The briefing proposes that the key policy areas are trade and domestic. In trade, the EU need to pursue market access for digital services, e.g. through the on-going WTO plurilateral negotiations on e-commerce. Domestic policy needs to focus on “equipping people to master digital technologies and adapt to change”: education, training, retraining and flexi-security, potentially paid for by taxing digital activities. It suggests that:

More than ever, societies with flexi-security policies, like the Nordic countries, which combine high quality education and people rather than job security, will be best prepared to manage the digital transformation.