Responsible AI governance is built through sustained, deliberate exchange with the people, institutions, and communities that AI systems most directly affect.

The Responsible AI Lab’s Engagement function tracks and publicly documents our presence at the intersection of industry, academia, and government. From federal agency listening sessions and state-level convenings to academic collaborations and industry roundtables, we track where RAIL shows up, who we are in conversation with, and what we bring to those conversations.

We believe that accountability begins with visibility. By making our stakeholder engagements public, we hold ourselves to the standard we ask of others — that influence over AI systems must be traceable, documented, and open to scrutiny.

Our engagements span four tracks:

Industry — Collaborations with financial institutions, technology developers and deployers, housing providers, and real estate associations navigating the promise and risks of AI adoption.

Academic — Research partnerships, conference presentations, and peer exchange with scholars advancing the science of algorithmic alignment, safety, and security.

Federal — Participation in agency listening sessions, advisory bodies, and interagency processes shaping national AI innovation and standards.

State & Local — Engagement with housing officials, fair housing organizations, and regional practitioners translating federal AI frameworks into on-the-ground practice.