Responsible GenAI at Scale: Open Source Commons and Governance

As generative AI rapidly transitions from experimentation to enterprise-scale deployment, the need for responsible, transparent, and governable systems has never been more urgent. This session explores how open source communities can play a foundational role in operationalizing Responsible AI at scale.

In the first half, the Generative AI Commons will introduce its Responsible AI workstream and the Responsible Generative AI Framework (RGAF), a community-driven framework designed to guide the development, evaluation, and deployment of trustworthy generative AI systems. Contributors from the community will share insights into how RGAF translates principles such as transparency, accountability, and safety into actionable practices across the AI lifecycle.

The second half features an interactive fireside chat with Kush Varshney, Ph.D from MIT, an IBM Fellow, and a long-time leader in AI research and development. Drawing from his experience at the IBM Thomas J. Watson Research Center, Dr. Varshney will discuss practical pathways to implement Responsible GenAI using open source tools and ecosystems. The conversation will highlight real-world projects, emerging standards, and how organizations can leverage open collaboration to move from principles to production.

Join us to learn how open source commons, frameworks like RGAF, and industry leadership are converging to shape the future of responsible generative AI.

Partners: Linux Foundation, Agencia Española de Supervisión de Inteligencia Artificial (AESIA)