Governance and Statistics Are Both Playing Catch Up in the Global Digital Economy

Information and communication technologies have been rewiring the global economy for more than a quarter of a century, with the side effect of decreased clarity around global flows of goods and services. The phenomenon of global supply chains in manufacturing is widely acknowledged: about three-fifths of trade in goods consists of components, so the idea of a final product being “made in” one country is highly misleading. However, it is only recently that the trade data has become available to make it possible to analyse trade in value-added terms.

Still, much more is known about tangible goods than about the growing intangible flows between nations. Multinationals have long allocated their financial transactions, leases, and intellectual property across economies based on a number of considerations, including to reduce their tax payments. These internal transfers are quite opaque. And two newer phenomena related to the digitalisation of economic activity are making it particularly difficult to analyse the modern global economy: contract manufacturing and cloud computing.

New technologies are blurring economic borders

Contract manufacturing (sometimes termed “factoryless goods production”) refers to the outsourcing (either domestically or overseas) of the actual production of goods while retaining ownership of the intellectual property and final products (and sometimes also raw materials or components). The contract manufacturer can be domestic or overseas. The initiating business will transmit blueprints or a patented set of instructions, often overseeing the production process in some detail, and take delivery of the finished product. It retains the high-value activities: the invention and design, and the sales and customer relationship.

It is far from easy to tell how widespread or how significant in scale this production structure is, but it is more widely used than is often appreciated. Many people will know that Nike does not manufacture shoes nor Apple smartphones (they are designed in California), but fewer will realise that, for instance, Mercedes does not manufacture its G Class SUVs; they are made in Austria by a Canadian-owned firm, Magna Steyr. Recent research based on web-scraped company data suggested that up to 18 percent of firms in some manufacturing sectors in the United Kingdom (particularly chemicals and pharmaceuticals), and 14 percent in the United States (particularly electronics and life sciences), state in their annual reports that they use contract manufacturers.

Still less is known about the scope of the use of cloud computing by businesses. This service offers firms the ability to store and transmit data, run software, and implement increasingly sophisticated techniques such as machine learning at low cost and high quality. The big digital companies—Amazon Web Services, Microsoft, Google, IBM—are the main providers globally. A range of indicators from industry experts and national bodies indicates that the volume of data being accumulated and transmitted within and between countries is skyrocketing. However, there are no comprehensive statistics on how much, or where this digital activity takes place.

More clarity, and a modern data governance framework needed

It is not even obvious how to think about this digitally enabled rewiring of the global economy. What are the implications if, say, a German auto manufacturer uses specialist designers in Sweden, sends data and intellectual property to plants in Brazil or Thailand, implements an international logistics chain for all the components, and uses a global cloud service provider with data centres in several European countries? Low- and middle-income countries need to think about the international connectivity aspects of where they fit into global supply chains. The digital divide is not only an issue within borders but across them too.

The absence of statistics matters too. The lack of clarity about the scope and scale of international intangibles and data flows certainly makes it harder to understand all the consequences of policy choices, including growing nationalism and protectionism.

The absence of an up-to-date framework for international governance of data is also an important challenge—as noted at the G20 Summit in Osaka earlier this year. Businesses face a patchwork of international legal and regulatory frameworks, with some jurisdictions seeking to assert theirs extra-territorially. Different countries have varying social norms concerning privacy. In several recent inquiries into competition in digital markets (in the European Union, United Kingdom, Australia, Germany, and Japan), data has featured as a potentially important barrier to innovation and competition, leading to an international conversation about common standards and inter-operability.

The development of artificial intelligence applications by governments and businesses is making this a more urgent task. There have been several initiatives to develop AI and data governance frameworks (including by the OECD, and CSIS), which focus on basic principles such as accountability, data freedom, interoperability, and so on. However, these general principles are some way from an international legal framework or set of norms.

Lessons learned

Are there lessons to be learned from the international governance of earlier technological innovations? In a recent workshop in Cambridge, we explored the governance frameworks for space technology, ICANN (the internet domain naming body), and embryology. Each developed in different historical and technological contexts: space during the Cold War when only large states were involved; ICANN emerging from the US government into an independent multi-stakeholder body; IVF following the UK’s Warnock Commission, which built consensus through a consultative process with citizens as well as experts and set a benchmark followed by many other countries.

Technological change is destabilising some of these governance frameworks. The proliferation of small privately-launched satellites is likely to lead to a big increase in the amount of space debris due to collisions and breakdowns. For instance, the European Space Agency recently had to avoid a collision with a SpaceX satellite in one of the proliferating private constellations of small satellites. In the case of embryology, it is the emergence of new and lower-cost genetic techniques that threatens the existing governance model. Earlier this year there was an international outcry when a Chinese researcher breached all protocols—including his own national regulations—by using new gene editing techniques on human embryos. Despite the condemnation, others plan to follow suit.

The lesson here is that international governance of a technology can accommodate national priorities and cultural preferences, but that it is also dependent on the technological and economic context. With new machine learning and AI technologies developing so rapidly, and data usage soaring, there is an urgent need for a comprehensive international framework responsive to the obstacles and opportunities for developing countries. The challenges are immense as well.