With data rapidly becoming the lifeblood of the global economy, the ability to improve its use significantly affects both social and private welfare. Data standardization is key to facilitating and improving the use of data when data portability and interoperability are needed. Absent data standardization, a “Tower of Babel” of different databases may be created, limiting synergetic knowledge production. Based on interviews with data scientists, this Article identifies three main technological obstacles to data portability and interoperability: metadata uncertainties, data transfer obstacles, and missing data. It then explains how data standardization can remove at least some of these obstacles and lead to smoother data flows and better machine learning. The Article then identifies and analyzes additional effects of data standardization. As shown, data standardization has the potential to support a competitive and distributed data collection ecosystem and lead to easier policing in cases where rights are infringed or unjustified harms are created by data-fed algorithms. At the same time, increasing the scale and scope of data analysis can create negative externalities in the form of better profiling, increased harms to privacy, and cybersecurity harms. Standardization also has implications for investment and innovation, especially if lock-in to an inefficient standard occurs. The Article then explores whether market-led standardization initiatives can be relied upon to increase welfare, and the role governmental-facilitated data standardization should play, if at all.
Bibliographical noteFunding Information:
The authors thank Daniel Francis, Avigdor Gal, Inge Graef, Scott Hemphill, Yoram Shiftan, Thomas Streinz, Eviatar Matania, and participants at the NYU Symposium on Data Law in the Global Economy and the biannual TILTing Perspectives Conference for wonderful comments on previous drafts; Benedict Kingsbury for helpful discussions; Eviatar Alkobi, Ilana Atron, Saar Ben Zeev, Ran Chaplin, Lior Frank, and Tamar Shtub for excellent research assistance; and the Center for Cyber Law and Policy at the University of Haifa for funding. Any mistakes or omissions remain the authors?.
© 2019 by Michal S. Gal & Daniel L. Rubinfeld.
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