Shaping the Future of AI Standardization

Abstract

In this keynote, Richard Tong, Chair of the IEEE Artificial Intelligence Standards Committee (C/AISC), explores the rapidly evolving landscape of AI and the critical role of global standardization in ensuring responsible, interoperable, and innovative AI systems. Drawing from IEEE’s expansive AI standardization portfolio, including foundational efforts like P3394 (LLM Agent Interface) and P3396 (AI Risk, Trust, and Safety), the keynote outlines strategic threads driving policy, governance, evaluation, and interoperability. With real-world insights from education and enterprise AI deployments, and ongoing collaborations with global academic and industrial leaders, the keynote also offers a vision for a cohesive AI ecosystem built on shared principles and open standards. Attendees will gain clarity on the path ahead for AI standards development and how to actively contribute to shaping the next generation of trustworthy and effective AI systems 

Biography

Richard Tong is a leading advocate for standardization and AI R&D collaboration between academia and industry.

  • Chair of the IEEE Artificial Intelligence Standards Committee.
  • Liaison from IEEE Computer Society to ISO/IEC JTC1 SC42.
  • Former Chair of IEEE Learning Technology Standards Committee.
  • Chair of IEEE 3394 LLM Agent Interface Standard Working Group. 
  • Co-chair of the 2025 IEEE Enterprise GenAI Summit (August 20-21, 2025| San Jose, CA https://www.computer.org/conferences/cfp-gen-ai-summit)
  • Co-chair of the Education Vertical Track of 2024 IEEE Conference on Artificial Intelligence in Singapore in June (https://ieeecai.org/2024/verticals/)
  • Co-chair of industry, innovation and practitioner track of AIED 2024 Conference in Brazil in July.
  • Co-founder of NEOLAF, the agent company for education.
  • Former Chief architect of Squirrel Ai Learning.
  • Deep experience in AI+Education and piloted and conducted AI+educationR&D programs with Stanford MediaXhttps://mediax.stanford.edu/featured-events/richard-tong-mediax2019/,  and CMU (as the program lead for “The CMU-Squirrel AI Research Lab on Personalized Education at Scale”  https://www.cs.cmu.edu/news/2019/cmu-yixue-education-inc-announce-ai-research-project-adaptive-k-12-education, University of Memphis, Columbia University, UC Berkeley, University of Florida
  • His research covers neuro-symbolic cognitive architecture, human-in-the-loop AI, trustworthy AI, self-improving agent, and multimodal reasoning. He is the main researcher of NEOLAF agent framework and the creator of OLAF adaptive instructional system stack.