Protecting people’s privacy is essential for fostering a trusted environment around the collection and use of data. Privacy also acts as a driver for data sharing and the generation of economic and social value. With the increasing complexity and unanticipated uses of personal data, especially in the case of AI, the utility of data protection and privacy becomes even more evident.

In response to this challenge, the OECD Privacy Guidelines are a solid foundation that helps governments, business, and civil society in their efforts to create a trust-based data ecosystem. They set out eight basic principles, namely collection limitation, data quality, purpose specification, use limitation, security safeguards, openness, individual participation, and accountability. This principle-based approach, combined with their technologically neutral drafting, enables the Privacy Guidelines to remain agile and adaptable to evolving technological and societal changes. 

Data is ubiquitous and the impact of data-driven innovation on privacy protection is contingent upon several domestic policy settings but also the nature and degree of international co-operation around data and data flows. International cooperation efforts are under way to build on multistakeholder experience across different countries, disciplines, sectors, and levels of government, within a common framework.  In particular, a holistic approach to international privacy cooperation requires: 

• Co-operation around high legal and technological standards of data security and data protection across the world;

• International cross-sectoral cooperation to avoid a siloed approach to data governance challenges;

• Strengthened cross-border privacy law enforcement to effectively protect individuals;

• Continued co-operation around transparency in practices of government access to personal data held by private companies.

As digital technologies evolve rapidly and are deployed globally, systematic cross-border collaboration in privacy enforcement is vital for achieving effective regulatory outcomes. 

There are a range of mechanisms for cross-border enforcement cooperation, ranging from mutual consultation, to parallel investigations through to joint design of remedies/penalties.

At any rate, collaboration is beneficial to amplify the impact of the global privacy enforcement community, ensuring an efficient use of public resources and given that not all Data Protection Authorities (DPAs) possess the same level of technical proficiency, especially concerning new and emerging technologies and their associated privacy risks or benefits. 

The importance of cross-border enforcement co-operation is central to the OECD’s work on privacy as enshrined in the OECD Recommendation on Cross-border Co-operation in the Enforcement of Privacy Laws. 

Artificial Intelligence (AI) offers both opportunities and challenges for international cooperation. The technology itself is ecosystemic, with its components dispersed worldwide. The advancement of AI depends on vast amounts of data from various territories. Innovations like generative AI accentuate the potential to memorise and infer personal attributes on a global scale. These factors highlight the need for clear guidance, alignment and cooperation on the different aspects of using personal data to fuel AI advancements. 

Despite the need for strong cooperation, the AI and privacy communities often engage in two separate spheres. As both communities share the same aim of promoting innovation while protecting human welfare, they could benefit from each other’s knowledge, experience, and priorities through greater collaboration. We at the OECD want to devote efforts to bring the AI and privacy communities together. The OECD.AI Expert Group on AI, Data, and Privacy provides a policy space to facilitate dialogue and alleviate possible misconceptions and mistrusts between the two communities.