The Algorithmic Learning Deficit: Artificial Intelligence, Data Protection, and Trade

Big Data and Global Trade Law, ed. by Mira Burri, Cambridge University Press, Forthcoming

18 Pages Posted: 18 Sep 2020

See all articles by Svetlana Yakovleva

Svetlana Yakovleva

University of Amsterdam - Institute for Information Law (IViR)

Joris van Hoboken

University of Amsterdam - Institute for Information Law (IViR)

Date Written: June 6, 2020

Abstract

Public policy interests implicated by international data governance and data flows, indispensable for the global governance of AI, stretch far beyond issues of economic growth and development. They also involve a broader set of national and regional priorities, such as national security, fundamental rights protection (such as the rights to privacy and to protection of personal data) and cultural values, to name just a few. Differences in the relative weight accorded each such priority when contrasted with the economic and political gains from cross-border data flows, have resulted in a diversity of domestic rules governing cross-border flows of information, especially when it relates to personal data, and a diversity of approaches to govern the use of AI in both private and public law contexts. Against this backdrop, this chapter’s aim is two-fold. First, it provides an overview of the state of the art in international trade agreements and negotiations on issues related AI, in particular, the governance of cross-border data flows. In doing so it juxtaposes the European Union’s (EU) and the United States approaches and demonstrates that the key public policy interests behind the dynamics of digital trade negotiations on the EU’s side are privacy and data protection. Second, building on the divergent EU and US approaches to governing cross-border data flows, and the EU policy priorities in this respect in international trade negotiations, this chapter argues that the set of EU public policy objectives weighted against the benefits of digital trade in international trade negotiations, especially with a view to AI, should be broader than just privacy and data protection. It also argues that an individual rights approach has limitations in governing data flows in the context of AI and should be expanded to factor in a clearer understanding of who wins and who loses from unrestricted cross border data flows in an age of data-driven services and service production.

Keywords: AI; International Trade; Digital Trade; Data Protection; Digital Sovereignty

Suggested Citation

Yakovleva, Svetlana and van Hoboken, Joris V. J., The Algorithmic Learning Deficit: Artificial Intelligence, Data Protection, and Trade (June 6, 2020). Big Data and Global Trade Law, ed. by Mira Burri, Cambridge University Press, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3668434 or http://dx.doi.org/10.2139/ssrn.3668434

Svetlana Yakovleva (Contact Author)

University of Amsterdam - Institute for Information Law (IViR) ( email )

Rokin 84
Amsterdam, 1012 KX
Netherlands

Joris V. J. Van Hoboken

University of Amsterdam - Institute for Information Law (IViR) ( email )

Rokin 84
Amsterdam, 1012 KX
Netherlands

HOME PAGE: http://www.ivir.nl/staff/vanhoboken.html

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