CAIHL read · Jun 8, 2026

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Reconciling how clinical reasoning is learned in the age of artificial intelligence

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.

How this item reads through CAIHL

Primary user

clinician

Clinicians or care teams are the primary users. Patients are affected downstream.

Hosting

institutional

Hosted inside a health system, insurer, or large employer. Access controlled by the institution.

Interests

patient-aligned

Interest structure prioritizes patients. Operates on a philanthropic, public-service, or advocacy footing.

Agency

neutral

Neither clearly expanding nor constraining patient agency.

One-sentence synthesis

Training-pipeline framing of AI-mediated clinical reasoning; the patient's interest in maintained reasoning skill is identified but not operationalized.

How this item appeared in the daily scan

Editor's note: If the next generation of clinicians is trained on a substrate that delivers the inference for them, the patient is talking to a clinician whose pattern recognition is borrowed. Borrowed pattern recognition fails on patients whose presentation is novel.

Summary: npj Digital Medicine: Perspective on what happens to medical-trainee clinical reasoning when AI tools handle the inferential heavy lifting — and how to preserve the reasoning skill the AI is replacing.

Read the original source →

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.