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CIPL Hosts Webinar on China’s Data Protection Landscape
Thursday, February 25, 2021

On February 23, 2021, the Centre for Information Policy Leadership at Hunton Andrews Kurth hosted a webinar on China’s Data Privacy Landscape and Upcoming Legislation.

During the presentation, representatives from CIPL and Hunton provided an overview of the increasingly complex data privacy and security landscape in China and examined key similarities and differences between China’s proposed Personal Information Protection Law (the “PIPL”) and the EU General Data Protection Regulation (the “GDPR”); representatives from Chinese-based private sector organizations discussed strategies and approaches for compliance with China’s data protection regime; and a leading academic from Beihang University provided an overview of the AI policy landscape in China.

Key highlights from the webinar include:

  • The data protection landscape in China is very extensive and undergoing continuous development. It includes dedicated data privacy legislation as well as a plethora of sectoral laws, regulations, guidelines and national standards dealing with data protection.

  • If passed, the draft Data Security Law and proposed PIPL, along with the Chinese Cybersecurity Law, would form the basis of a comprehensive system of data protection in China. The PIPL and the draft Data Security Law are likely to pass into law at some point in 2021, along with some additional implementing rules.

  • Given the many similarities between the PIPL and the GDPR, organizations are thinking about how to leverage GDPR compliance efforts to prepare for compliance with the PIPL and how to identify and bridge relevant gaps. In addition, organizations are exploring the similarities between the PIPL and many existing regulations and standards in China to leverage compliance efforts in anticipation of the PIPL.

  • China’s AI policy landscape is also developing rapidly with calls for the formation of new regulations for algorithm-based recommendations, deep fakes and other aspects of AI.

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