Caleigh Curley

Listening to the Circle: Using AI to Support Talking Circles on Medicaid Enrollment in the Navajo Nation

This project explores how artificial intelligence (AI) can ethically and
meaningfully support research by assisting in the transcription and thematic analysis of
community talking circles focused on Medicaid enrollment barriers in the Navajo Nation. Talking
circles are a traditional and relational way of sharing knowledge, grounded in Diné philosophy.

The project will use AI tools to respectfully listen to and transcribe audio recordings from these
circles—held with Tribal health leaders, community members, and caregivers—and assist in
identifying themes that reflect the lived experience of navigating Medicaid systems. These
insights will inform community-led recommendations aimed at improving access, upholding
sovereignty, and addressing long-standing structural barriers across state and federal systems.
This work is being conducted as part of the Caleigh’s doctoral dissertation. It has been
approved by both the University of Arizona Institutional Review Board and the Navajo Nation
Human Research Review Board.

By centering Indigenous values and voices, the project offers a humanistic model for how AI can
support, rather than supplant, relational research and policy advocacy in Tribal contexts.
Narrative Summary and Student Engagement with AI Creative Approaches to Complex Societal
Challenges. This project addresses the under-enrollment of Navajo citizens in Medicaid, a critical
issue that impacts Tribal healthcare funding and access. Rather than relying on top-down data
analysis, this project draws on the traditional practice of talking circles to gather insights directly
from those most affected.

AI tools will be used only in supportive roles—specifically, for transcribing audio recordings and
identifying common themes through natural language processing—to ease the labor of analysis
and ensure that no voice is lost. Students will creatively combine Indigenous methodologies
with AI-assisted workflows to surface community-driven understandings of structural and
cultural barriers to healthcare access. Addressing Ethical, Cultural, and Community-Based
Impacts of Technology Respect for Indigenous data sovereignty is central.

The use of AI in this project follows the CARE Principles and TribalCrit, ensuring that data from
talking circles remains under the control of the community and is used solely for community
benefit. AI will not make decisions or interpretations; it will only assist in transcribing and
organizing voices for human review. Students will engage in dialogue about the ethical
boundaries of AI in Indigenous spaces, including how technologies can reinforce or disrupt
relational knowledge systems. All transcripts and themes will be validated through community
review before inclusion in any public materials. As required by both IRBs, data sharing and
consent protocols are designed to protect individual and collective rights.

Showcasing the Influence of Humanistic Knowledge in AI The project is grounded in Indigenous
humanistic frameworks—Diné language, philosophy, storytelling, and collective wisdom, 
students will reflect on how AI can support, rather than erase, these forms of knowledge. For
instance, rather than treating spoken words as data points, AI transcription will be framed as a
way to listen deeply and preserve oral narratives. The thematic outputs will be treated not as
final conclusions but as conversation-starters for further dialogue, always grounded in respect,
consent, and community control. Building Transferable Skills for a Rapidly Changing Workforce
Students will gain hands-on experience using AI transcription tools (e.g., Whisper or Otter.ai)
and qualitative coding software (e.g., MAXQDA, Atlas.ti) with AI-assisted capabilities. Just as
importantly, they will learn to work within Tribal IRB frameworks, conduct respectful
community-based research, and grapple with the cultural and ethical responsibilities of working
with AI in Indigenous contexts. These skills will prepare students to lead in a workforce that
increasingly demands both technical fluency and cultural competence.

Research Aims
1. Facilitate Talking Circles with Tribal Health Stakeholders. Organize a series of talking circles
with community members, health professionals, and caregivers on Medicaid navigation and
enrollment challenges.
2. Use AI to Transcribe and Identify Themes. Apply AI tools to transcribe circle recordings and
assist in surfacing recurring themes. Ensure all outputs are reviewed and validated by
community partners.
3. Support Community-Led Recommendations and Dissemination. Share findings with the
Navajo Epidemiology Center, Navajo Human Research Review Board, and other partners to
inform policy and program improvements.

This project is led by Caleigh, an Indigenous student researcher, as part of their doctoral dissertation at
the University of Arizona. Caleigh will coordinate logistics, conduct talking circles, use AI
transcription tools, analyze qualitative data, and present findings to Tribal stakeholders.

All materials, including transcripts and thematic findings, will be reviewed and approved by the
Navajo Nation Human Research Review Board and shared in accordance with Tribal protocols.
Community members will co-author or co-present findings, and summaries will be made
available in both English and Navajo. Outputs will be shared with Tribal leaders, state Medicaid
offices, and Indian Health Service partners to advance equitable solutions.

This project reimagines AI not as a decision-maker, but as a respectful listener. By assisting with
the transcription and analysis of talking circles on Medicaid access, AI can support the
transmission of community voices into policy discussions. This student-led initiative, approved
by both the University of Arizona and the Navajo Nation IRBs, offers a model for how emerging
technologies can be grounded in Indigenous knowledge systems to meet urgent public health
challenges with cultural care and relational integrity.