Global Governance of AI Products and Use? Still a Good Approach for MNCs?

Sun Hee Kim, Partner, Yulchon

Sandy Kunvatanagarn, Head of Policy, APAC, OpenAI

Lorraine Lee, CIPP/E, CIPM, Founder, Principal Consultant, NorthStar Data Privacy

Gil Zhang, CIPP/A, CIPP/CN, CIPP/E, CIPM, FIP, Partner, Fangda Partners 

Over the past seven years, as many companies implemented data protection programs to work with the GDPR and other data protection legislation in the many countries where they operate, many seem to believe that having a unified global data protection initiative is a good approach. This assumption seems to have been tried and tested in recent years, but some wonder whether this is still a good approach in reality. The U.S., China and Europe, and now even South Korea, each have different approaches to AI regulations, which has led to market fragmentation for existing AI companies and tech giants. How do you offer online services with AI tools that are available globally? Would a principle-based governance approach be sufficient? How do you address potential misinformation, inaccuracy and bias using data globally while meeting cross-border data transfer requirements? 

What you will learn:

• How U.S., China, EU and South Korea’s regulations are shaping AI regulatory framework and the reality that AI companies operate in now. 
• Pros and cons of having an AI governance framework that works globally. 
• Good tools and approaches to evaluate AI products in multiple countries and design products and solutions with the least divergence.  
• How to address potential misinformation, inaccuracy and bias using data globally, while meeting cross-border data transfer requirements.