CAIHL read · Jun 6, 2026
Online Safety Regulation Increases Privacy Risk: Evidence from the UK Online Safety Act
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
patient
Patients, families, and care partners are the primary users of this AI.
Hosting
government
Hosted or controlled by a government agency or program.
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
Safety regulation producing a privacy externality; constraining agency in the population the regulation was designed to expand it for.
In the scan
How this item appeared in the daily scan
Editor's note: Safety regulation that produces a privacy externality is the canonical pattern. The next state-level chatbot bill that requires age verification before mental-health chat access will run into the same finding.
Summary: arXiv preprint: Empirical analysis of the UK Online Safety Act demonstrating that the mandated age-verification and content-moderation requirements have increased privacy-risk exposure for the same users the Act was written to protect.
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.