CAIHL read · Jun 5, 2026
Why AI has outpaced medical malpractice law, and what to do about it [PODCAST]
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
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
Voice of clinician concern about AI liability gap; constraining because the law has not yet built a patient-protective layer.
In the scan
How this item appeared in the daily scan
Editor's note: The clinician's liability shield against AI tooling does not exist. The patient's liability shield against AI tooling does not exist either. Two parties have absorbed a third party's risk, and the third party is the vendor.
Summary: KevinMD: Podcast episode framing the central litigation problem — when a clinician adopts an AI tool whose decision logic the clinician cannot inspect, the malpractice liability falls on the clinician under doctrine designed for human decisions and human errors.
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.