CAIHL read · Jun 4, 2026

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Mapping AI regulation in health care with the Health & AI Policy Index (HAPI)

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

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

patient-aligned

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

Agency

expanding

Expands patient capabilities, supports their questions, increases their ability to act on their own values across and beyond health systems.

One-sentence synthesis

Policy-mapping artifact that patient advocates can cite when an institution claims regulatory cover.

How this item appeared in the daily scan

Editor's note: HAPI is the first artifact patient advocates can cite when an institution claims regulatory cover. Use it to ask which of the 240 policies actually constrains the AI in front of you.

Summary: npj Digital Medicine: Mount Sinai researchers analyze 240 health-AI policies from 2016-2025 across 100+ issuers, finding fragmented oversight, transparency-oriented advisories dominant, obligations falling on providers and developers.

Read the original source → · CLAIM analysis →

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.