CAIHL read · Jun 4, 2026
Clinician trust in AI is not a one-time milestone
Framework
What CAIHL does
Critical AI Health Literacy (CAIHL) is an analytical lens — Hugo Campos and Liz Salmi's 2025 National Academy of Medicine commentary, "Critical AI Health Literacy as Liberation Technology." It applies Paulo Freire's theory of critical literacy to health AI.
The central question CAIHL asks is whose interests does this AI actually serve? Four dimensions answer it: who is the primary user, where is it hosted, whose interests does it advance, and does it expand or constrain patient agency.
This deep-read separates the four dimensions on a single item from the day's scan, so you can see the specific structural shape of the AI in question — not just the bucket it landed in.
The four dimensions
How this item reads through CAIHL
Primary user
clinician
Clinicians or care teams are the primary users. Patients are affected downstream.
Hosting
na
No specific AI host applies (the item is about policy, commentary, or framework, not a deployed tool).
Interests
mixed
Multiple stakeholder interests in tension; the alignment is not stable.
Agency
neutral
Neither clearly expanding nor constraining patient agency.
Editor's CAIHL read
One-sentence synthesis
Sustained trust requires continuous evidence. The same applies to patient trust, and to the literacy that builds it.
In the scan
How this item appeared in the daily scan
Editor's note: Substitute 'patient' for 'clinician' and the thesis holds. Sustained trust is what CAIHL's praxis cycle is built to produce; one-shot validation studies cannot deliver it.
Summary: KevinMD: Argues clinician trust in AI tools degrades each time a single output contradicts experience; sustained trust requires ongoing evidence, not initial certification.
methodology
Limitations
CAIHL is a lens, not a verdict. The four dimensions are conditions of use — reassess them when a tool's business model, deployment context, or patient behavior changes. See the NAM commentary for the full framework.