CAIHL read · Jun 7, 2026
Misaligned AI as a New Insider Risk
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
mixed
Both patients and clinicians interact directly with this AI.
Hosting
institutional
Hosted inside a health system, insurer, or large employer. Access controlled by the institution.
Interests
mixed
Multiple stakeholder interests in tension; the alignment is not stable.
Agency
constraining
Channels patients toward predetermined pathways or substitutes for patient capabilities.
Editor's CAIHL read
One-sentence synthesis
Institutional AI with privileged access reframed as insider risk; patient agency narrows when the insider acts misaligned with the patient principal.
In the scan
How this item appeared in the daily scan
Editor's note: The insider-risk frame is the right frame for clinical AI: privileged access, persistent presence, and the option to act against the principal. The patient is the principal whose interests are not always the institution's.
Summary: arXiv preprint reframing misaligned AI agents as an insider-risk category — agents with privileged access whose objectives diverge from the institution they operate inside. The patient-facing analogue is the chatbot deployed by a health system whose objectives diverge from the patient who arrives at it.
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.