MIT Critical Data · Digital Ethnography
Voices of AI
in Medicine.
A global, community-owned digital ethnography affiliated with documenting how healthcare learners and early-career professionals experience artificial intelligence in real time.
An archive that captures how AI is experienced, interpreted, and negotiated within institutional and social contexts — before institutions stabilize meaning.
Our Mission
An ecosystem for understanding AI in healthcare
We document lived experience
We collect 5-minute audio and video narratives in participants' native languages, capturing how AI is encountered in coursework, clinical settings, peer conversations, and personal experimentation.
We build a global research archive
Contributions are collected continuously, allowing the project to evolve alongside changing technologies, policies, and social norms. The platform functions as a living document that also captures silences, hesitations, and omissions.
We center underrepresented voices
Geographic and cultural diversity is analytic material. We actively recruit from regions typically absent from global AI discourse, supporting participants in any language.
Confessionals & Testimonials
Personal narrative over academic abstraction
This approach is intentionally longitudinal and open-ended. Contributions are collected continuously, allowing the project to capture not only what is said about AI in medicine, but how conversations shift, intensify, or fall silent over time.
A core innovation is the systematic treatment of non-speech as data. Silence, hesitation, humor, and indirect language are analyzed as meaningful responses to power and evaluative pressure.
Audio & Video
5-min recordings in your native language
Group Sessions
Classmates, friends, and family together
Personal Stories
Lived experience, not academic theory
AI Analysis
Thematic analysis, human-interpreted
Key Research Questions
Understanding how attitudes toward AI are formed
What experiences inform attitudes toward AI?
Encounters with policies, peer guidance, AI tools in coursework, and personal experimentation
What themes emerge across cultures?
How local educational structures, healthcare systems, and cultural norms shape conversations
What is not being discussed?
Silences, self-censorship, fear of institutional reprisal, and 'algorithmic superstition'
Echo chambers vs. diverse perspectives?
Comparing insular narratives with those that emerge through cross-cultural dialogue
Participate
Who can contribute
This project centers on those who encounter AI within environments shaped by learning, evaluation, and institutional power. These individuals often experiment with AI tools early in practice, yet rarely influence how institutions govern those tools.
Participation extends beyond clinical training to include engineers, humanists, artists, and other collaborators whose work intersects with medicine. Contributors may participate individually or in small groups.
Geographic and cultural diversity is analytic material. Participants speak in their preferred languages while translation supports interpretation.
Open to
Potential Impact
A time-sensitive record before institutions stabilize meaning
For Researchers
A time-sensitive archive documenting how AI enters medical training before institutions stabilize meaning
For Educators
Identify gaps between formal AI policies and lived practice to inform curriculum reform
For Policymakers
Equity-oriented governance insights showing how attitudes vary by role, region, and institutional power
Clear guardrails prohibit use of the archive for surveillance, performance evaluation, or predictive profiling. Participants retain the right to withdraw contributions or reduce their visibility as circumstances change.
Add Your Voice.
Share a 5-minute audio or video recording describing your personal moments, tensions, and reflections related to AI in your educational, clinical, or creative life.
Get Involved