HELIOS Lab, Stanford Medicine

I joined the HELIOS Lab (Stanford Medicine) as a graduate researcher the first quarter at Stanford. HELIOS was part of AI-READI, a consortium under the NIH Bridge2AI initiative focused on type II diabetes data collection. AI is moving fast into biomedical research, but Indigenous Peoples (whose data, land, and communities are directly affected) are often not consulted in the design and governance of these tools. This project spun out from the work of AI-READI, and focused on the enabling conditions for good research practices and ways in which Indigenous governance can be strengthened.

I started this endeavor by synthesizing peer-reviewed literature on AI governance, Indigenous data sovereignty, and community-engaged research practices, then built our interview protocol. Between me and the PhD candidate I worked with, we conducted 30 interviews of Indigenous scholars and Tribe members, asking myriad questions about data sovereignty, relationship building, and AI/ML usage within the context of medical research. Data collection was slow and intentional, as we were constantly seeking to build trust with the colleagues and Tribal community members we engaged with.

Two years later, we are still writing and synthesizing our work for publication, but also have pivoted towards design work born from insights in these interviews. After presenting and validating our initial findings to Tribal Council in April 2026, I pivoted my work towards building ready-to-ship tools for Tribal community use. These tools are built using a set of design principles:

All outcomes of this research (a white paper, contract review tools, partnership screenings) are built squarely for the Tribe we’re working with. They have ultimate say of whether our work is published and shared with the world, corresponding with our core value of data sovereignty and strengthened governance.