CAIHL read · Jun 7, 2026
Generative Models Erode Human Temporal Learning Through Market Selection
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
public
Hosted for public use (ChatGPT, Claude, consumer apps). Anyone with a device can use it.
Interests
commercial
Prioritizes vendor or platform commercial interests (advertising, data, retention).
Agency
constraining
Channels patients toward predetermined pathways or substitutes for patient capabilities.
Editor's CAIHL read
One-sentence synthesis
Market-selected generative tools as cognitive offload; constraining patient agency in the temporal-learning layer most relevant to chronic disease.
In the scan
How this item appeared in the daily scan
Editor's note: If generative systems erode temporal learning, the clinician who outsources pattern recognition to AI is the lab patient. The chronically-ill patient who outsources symptom-tracking to a wellness app is the other one.
Summary: arXiv preprint: Generative models, deployed at scale through market mechanisms, may erode the human capacity for temporal learning — pattern recognition over time — because the user no longer needs to maintain the model the system maintains for them.
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.