Fitting Machine-Generated Data into Trade Regulatory Holes

The Trade in Knowledge: Economic, Legal and Policy Aspects, Antony Taubman and Jayashree Watal, eds., Cambridge University Press, 2020, Forthcoming

Texas A&M University School of Law Legal Studies Research Paper No. 19-28

17 Pages Posted: 25 Jun 2019

See all articles by Peter K. Yu

Peter K. Yu

Texas A&M University School of Law

Date Written: June 25, 2019

Abstract

In an era when the Internet of Things has slowly transformed into the Internet of Everything, data generated or collected by networked sensors, interconnected devices and intelligent machines have been highly valuable. Taking note of the data's enormous and ever-growing value and the unlimited potential for their use and reuse, industries and their supportive policy makers have actively pushed for greater protection of machine-generated data.

In October 2017, the European Commission proposed a new sui generis data producer's right for nonpersonal, anonymized machine-generated data. If countries began to create new rights in machine-generated data—whether based on the EU proposal or other proposals—the cross-border flow of such data would raise questions about the need for new trade standards. Additional complications would also arise over the potential incoherency between these new trade standards and those other standards that have already been developed, or are now being developed, at bilateral, regional, multilateral and plurilateral fora.

In view of this emerging trade policy debate, the present chapter highlights two sets of challenges concerning the development of new trade standards for regulating the cross-border flow of machine-generated data:

(1) national policy development and

(2) international norm setting.

The chapter begins by identifying five sets of policy questions that have to be addressed before the creation of a new national regime for the protection of machine-generated data. The chapter then turns to the potential complications that would arise in the international norm-setting arena. Taken together, these two sets of challenges show how the protection, regulation and overall governance of machine-generated data may not fit well with the existing international trade regime.

Suggested Citation

Yu, Peter K., Fitting Machine-Generated Data into Trade Regulatory Holes (June 25, 2019). The Trade in Knowledge: Economic, Legal and Policy Aspects, Antony Taubman and Jayashree Watal, eds., Cambridge University Press, 2020, Forthcoming; Texas A&M University School of Law Legal Studies Research Paper No. 19-28. Available at SSRN: https://ssrn.com/abstract=3409532

Peter K. Yu (Contact Author)

Texas A&M University School of Law ( email )

1515 Commerce St.
Fort Worth, TX 76102
United States

HOME PAGE: http://www.peteryu.com/

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