Regulating Cross-Border Data Flows: Harnessing Safe Data Sharing for Global and Inclusive Artificial Intelligence
Tshilidzi Marwala, Eleonore Fournier-Tombs and Stinckwich, Serge (2023). Regulating Cross-Border Data Flows: Harnessing Safe Data Sharing for Global and Inclusive Artificial Intelligence. UNU Technology Brief. United Nations University.
Document type:
Report
Collection:
-
Attached Files (Some files may be inaccessible until you login with your UNU Collections credentials) Name Description MIMEType Size Downloads UNU-TB_3-2023_Regulating-Cross-Border-Data-Flows.pdf English PDF 
application/pdf 480.30KB UNU-TB_3-2023_Regulating-Cross-Border-Data-Flows_JP.pdf Japanese PDF
application/pdf 684.26KB -
Author Tshilidzi Marwala
Eleonore Fournier-Tombs
Stinckwich, SergeTitle Regulating Cross-Border Data Flows: Harnessing Safe Data Sharing for Global and Inclusive Artificial Intelligence Series Title UNU Technology Brief Volume/Issue No. 3 Publication Date 2023-10 Place of Publication Tokyo Publisher United Nations University Pages 7 Language eng Abstract In an increasingly interconnected world, data movement across international borders has become crucial to economic development, innovation and social advancement in an age of interconnected global networks. The international flow of data contributes to economic growth by fostering innovation, enhancing productivity, and facilitating international trade. However, calls to reduce barriers to cross-border data flows have sparked concerns regarding privacy, security, and data protection. The critical policy issue related to cross-border data flows is their potential restriction, particularly through data localization requirements. These requirements force organizations to restrict data access, sharing, and re-use within national borders. However, such restrictions can harm the functioning of markets and the prosperity of societies by limiting the benefits of sharing and re-using data across countries. Nevertheless, it is critical to proportionally address risks, consider the sensitivity of data and understand the purpose and context of processing. Cross-border data flows are becoming increasingly important in the global artificial intelligence (AI) conversation. The ability to freely and securely transfer data across borders allows AI systems to access diverse information, which is an essential element of debiasing and democratizing AI. However, the emerging patchwork of regulatory approaches to data flows could hinder the deployment of AI systems globally, restrict access to data, and require the duplication of technologies and effort because of data location fragmentation. Therefore, to fully reap the benefits of AI, more interoperable regulatory approaches that enable the free flow of data with trust are needed. Copyright Holder United Nations University Copyright Year 2023 Copyright type All rights reserved ISBN 9789280891454 -
Citation counts 
Search Google Scholar
Access Statistics: 175 Abstract Views, 401 File Downloads - Detailed Statistics Created: Thu, 26 Oct 2023, 15:37:18 JST by Powell, Daniel on behalf of UNU Office of Communications