People who resist surveillance object to it and try to prevent it. People who acquiesce to surveillance object to it but do not try to prevent it. Instead, they exchange information in ways required by informational norms. They do so to avoid trouble and get on with their lives. Acquiescence takes two forms – one when the party conducting surveillance is also a party to the norm, and one when it is not. In both cases, acquiescence leads to a compromised selective flow of information that reduces privacy in public.

The chapter explores the concept of data portability in a data-driven world. In the first part, it maps out the journey data takes in a data economy and investigates the valuation and cost of data. It posits that, because of data analytics, machine learning, and artificial intelligence models, “generated” data, as data that has been derived or inferred from “raw” data, is of higher value in the data market, and carries a higher cost of production. In the second part, building on this taxonomy, the requirements for the free flow of data in competitive data-centric markets are discussed: regulations on data tradability and portability. The analysis leads to doubt that the newly introduced and widely debated rules regarding portability of data under European Union law will adequately provide these prerequisites. The chapter concludes by suggesting an alternative model for data portability: rather than distinguishing between personal and non-personal data, the legal concept of data portability should be based on the allocation of value; that is, whether the value of data provides cost compensation to the service provider. Raw data should always be portable, while generated data may require a more refined regime depending on whether it is compensating costs.

The law as a structural system attempting to stabilize the social order is confronted with far-reaching technological advances that have the potential to undermine traditional normative principles. Particularly in a digital and globalized environment, a broader and better coordinated rule-making approach is needed. Legal interoperability as process of making normative rules cooperate across jurisdictions to avoid a fragmented landscape gains importance. In view of the technological innovations an appropriate international framework for the data-driven world should implement three basic regulatory principles, namely (i) transparency, (ii) accountability, and (iii) safety and robustness, leading to trust and traceability. Furthermore, such a framework must contribute to the avoidance of distortions caused (i) by an anticompetitive behavior of market dominant enterprises, (ii) by a not justified denial of network neutrality, and (iii) by the imposition of inappropriate data localization rules. A new digital trade regime overcoming the outdated goods’ and services’ classifications and encompassing international regulatory cooperation is also needed in view of overcoming the present tensions in WTO law and of developing an appropriate framework for digital assets. The new business models with tokenized values must become part of the trade rule framework with regulatory elements being an enabler of digital innovation.

This chapter outlines several ways that autonomous organizations will put pressure on existing law and will perhaps require accommodations from the law in the future. In particular, legal concepts like fraud that require “intent” may become less workable as more legal action is taken by systems that lack the capacity for intent. Moreover, if perpetually autonomous organizations become more commonplace, the law will need to pay attention to the possible drift between their initial operating agreements and future states of affairs, whether because of the possibility of “hacking” or simply because general circumstances have unexpectedly changed.

Artificial intelligence technologies have brought to humanity benefits and challenges. Some AI products can be used to threaten non-trade values including fundamental rights and national security. “Data-sharing policies”, through which governments “feed” data into their AI industry, further raise fair competition concerns. At present, economic sanctions taken by trade powers play an important role in deterring the controversial use of AI policies. In this chapter, it is argued that the WTO law can offer some aid in disciplining AI policies. First, some “data-sharing” mechanisms may be challenged as actionable subsidies under the WTO law. Second, sanctions against AI policies that undermine fundamental rights or national security may not be found inconsistent with WTO law due to, inter alia, the “public morals” exception, the security exception and the “maintenance of international peace and security” exception. Accordingly, it is argued that WTO law can provide some assistance in the disciplining of “data-sharing” mechanisms and AI policies that undermine fundamental rights or national security.

This chapter argues against several intuitively plausible but misguided arguments against autonomous organizations, and it defends those organizations as a matter of policy in view of their flexibility and the opportunities they create for innovation.

Since the issuance of a joint statement in January 2019, seventy-eight World Trade Organization (WTO) members have confirmed their intention to commence WTO negotiations on trade-related aspects of electronic commerce. There is a growing expectation that a new agreement on trade-related aspects of electronic commerce (TREC Agreement) will be adopted in the not-so-distant future. One key question that has been left out in the process of negotiating the TREC Agreement is how disputes concerning electronic commerce should be settled. This chapter points out that digital trade disputes arising under the proposed TREC Agreement will likely differ from conventional trade disputes arising under the WTO agreements in terms of the diversity of stakeholders and the nature of the balance between trade and non-trade values and that the rules and procedures of the WTO Dispute Settlement Understanding (DSU) may not properly apply to the former. It argues that special or additional dispute settlement rules and procedures should be incorporated into the TREC Agreement to fill those gaps in the existing DSU with regard to the handling of digital trade disputes.

The EU only recently put AI at the top of its political agenda. However, data flows that are essential for the development of AI will need to fulfill European legal requirements. This chapter assesses whether the European legal framework on data protection may have an impact on the development of AI-based technologies. Given the size of the single market, European legal regulation of data flows inevitably produces legal effects outside the European territory. Those limitations may be challenged internationally as they constitute obstacles to trade for foreign companies and EU partners. The EU position tries not to be perceived as protectionist and promotes free flows of data that are essential for digital companies, in particular those developing the AI industry. This European way of dealing with digital trade and data flows in trade agreements is not shared by its trade partners. The contrast between the content of EU trade agreements and proposals and the last US free trade agreement illustrates how a possible transatlantic conciliation seems presently hard to attain. More broadly, fragmentation and new forms of sovereigntisms should continue to characterize the international free movement of data regime and impact future AI development.

The trade war between the USA and China that started around 2018 exposed the vulnerability of the international trade law regime anchored on the WTO. This essay explores the possibility that the escalating conflict between the world’s two most powerful economies may be resolved in emerging global markets defined not by an information revolution but by a knowledge revolution. The conventional wisdom among Western pundits discounts the possibility that China might emerge as victorious in a contest with the West to decide who is best at advancing the frontier of knowledge. America won the last global knowledge economy “land rush” triggered by the commercialization of the Internet. Early evidence suggests the next great global knowledge economy land rush will be fueled by innovations including artificial intelligence, mobile computing, cloud computing, social production and the Internet of Things, with early evidence showing it might well be won by China. If this were to occur, then the international trade law regime might continue to drift away from the WTO framework based on Westphalian notions of public international law and may drift closer to China’s distinctive legal institutions and traditions.

This chapter introduces three cross-cutting themes that illustrate the relationship between artificial intelligence and international economic law (IEL): disruption, regulation, and reconfiguration. We explore the theme of disruption along the trifecta of AI-related technological, economic, and legal change. In this context, the impact of AI triggers political and economic pressures, as evidenced by intensive lobbying and engagement in different governance venues for and against various regulatory choices, including what will be regulated, how to regulate it, and whom should be regulated. Along these lines, we assess the extent to which IEL has already been reconfigured and examine the need for further reconfiguration. We conclude this introduction chapter by bringing the contributions we assembled in this volume into conversation with one another and identify topics that warrant further research. Taken as a whole, this book portrays the interaction between AI and IEL. We have collectively explored and evaluated the impact of AI disruption, the need for AI regulation, and directions for IEL reconfiguration.

The convergence of AI, robotics, 3D printing, blockchain and the Internet of Things into digitally connected networks of production, communication and consumption is driving the Fourth Industrial Revolution. Recent notifications of draft regulations to the TBT Committee show that Industry 4.0-related regulations are increasing in number and variety. There is a risk that the interconnectivity and interoperability required by Industry 4.0 could be hampered by discriminatory or unnecessarily divergent standards and regulations. This chapter discusses how the existing principles and disciplines in the TBT Agreement as well as practices and guidance developed by the WTO TBT Committee could help avoid unnecessary regulatory diversity and reduce trade costs. It argues that the TBT Agreement, by promoting global regulatory coherence (harmonization via international standardization) and global regulatory cooperation and convergence (via Good Regulatory Practices, Equivalence, Mutual Recognition), will assume even greater importance as standards and regulations are developed for Industry 4.0.

This chapter surveys a number of regulatory interventions through which governments seek to enhance domestic companies’ access to data: mandatory data sharing requirements (as under the EU’s new financial services regulations), data transfer restrictions (as under India’s draft ecommerce policy), and open data initiatives (as under Singapore’s ‘smart nation’ initiative) – all seek to make more data available with the aim of spurring innovation and growth in the AI economy. Such measures are indirectly affected by existing and newly emerging rules of international economic law. International investment law is likely to be mobilized in defense against governments that seek to mandate data sharing from private data holders, while new rules on “digital trade” are meant to ensure transnational data mobility. In sum, international economic law regulates data in favor of data-holders’ ability to retain control over data location and use and constrains states’ ability to confront asymmetric control over data.

This chapter introduces three cross-cutting themes that illustrate the relationship between artificial intelligence and international economic law (IEL): disruption, regulation, and reconfiguration. We explore the theme of disruption along the trifecta of AI-related technological, economic, and legal change. In this context, the impact of AI triggers political and economic pressures, as evidenced by intensive lobbying and engagement in different governance venues for and against various regulatory choices, including what will be regulated, how to regulate it, and whom should be regulated. Along these lines, we assess the extent to which IEL has already been reconfigured and examine the need for further reconfiguration. We conclude this introduction chapter by bringing the contributions we assembled in this volume into conversation with one another and identify topics that warrant further research. Taken as a whole, this book portrays the interaction between AI and IEL. We have collectively explored and evaluated the impact of AI disruption, the need for AI regulation, and directions for IEL reconfiguration.