CAIHL read · Jun 4, 2026

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Patients' Use Of AI To Find Doctors Doubles In 9 Months

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

patient

Patients, families, and care partners are the primary users of this AI.

Hosting

public

Hosted for public use (ChatGPT, Claude, consumer apps). Anyone with a device can use it.

Interests

patient-directed

Patient controls when and how the AI is used.

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

Patient-directed AI for provider search doubled in 9 months. 45-60 cohort leads, not Gen Z.

How this item appeared in the daily scan

Editor's note: The age inversion is the headline: middle-aged patients are leading AI adoption for provider search, not Gen Z. The reputation-management vendor sees this first because it sells against it.

Summary: MediaPost: rater8 report finds AI use to research providers jumped from 17% to 36% in 9 months; 45-60 age cohort leads adoption at 64%, well ahead of 18-29s at 28%.

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.