On October 16, 2025, the Institute for AI International Governance (I-AIIG) at Tsinghua University hosted an online lecture titled “AI-Driven Global Standardization: The MPAI Framework and Cross-Sector Practices.” The session featured Dr. Leonardo Chiariglione, Founder of MPAI (Moving Picture, Audio and Data Coding by Artificial Intelligence) and a pioneering figure in international standardization. The session was moderated by Professor Liang Zheng, Vice Dean of I-AIIG.
Dr. Chiariglione provided an overview of MPAI’s ecosystem and operational framework, emphasizing the importance of interoperability in AI systems. “Standardization is key to enabling AI models from different domains to work together effectively,” he said. “Through common frameworks, we can build a more efficient and trustworthy AI ecosystem.”
Using Connected Autonomous Vehicles (CAV) as a case study, Dr. Chiariglione elaborated on MPAI’s standard framework for autonomous driving systems, highlighting critical aspects such as data representativeness, authorization, privacy, and reliability. He described the data flow within subsystems and stressed the importance of safety and data integrity in the decision-making chain. “Establishing early warning mechanisms is essential to ensure system trustworthiness and robustness,” he noted.
In the Metaverse domain, Dr. Chiariglione outlined MPAI’s approach to developing operational standards that govern interactions between human-driven virtual avatars and autonomous AI agents. He discussed how AI can enable personalized, emotional, and verifiable interactions in virtual environments, shaping the next generation of immersive experiences.
The lecture also addressed ethical, legal, and performance evaluation issues in AI standardization. Dr. Chiariglione emphasized that “Technical performance must always go hand in hand with fairness, bias prevention, legal compliance, and safety.”
Concluding his talk, Dr. Chiariglione reflected on the global evolution of AI standards and intellectual property frameworks, calling for deeper cooperation between academia and industry to advance research and governance in generative AI and metaverse technologies. “Only through international cooperation can we shape a sustainable and equitable future for AI,” he concluded.
