Raw LLM Responses

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Comment
Love the prism example, but I would like to reframe what I believe happens: The chatbot points wrong. That's a CLAIMED output — the model generated an answer based on its processing pipeline. The human looks at it and says "that's wrong, and here's why — there's a prism distorting your input." The human didn't fix the answer. The human diagnosed the process. Found the abstraction layer where reality got bent. Then the model recalibrates — not by memorizing "the object is actually over here," but by understanding that its pipeline has a systematic distortion that needs to be modeled. That's not a correction. That's a governance event.
youtube AI Moral Status 2026-03-02T15:2…
Coding Result
DimensionValue
Responsibilitynone
Reasoningconsequentialist
Policynone
Emotionindifference
Coded at2026-04-27T06:24:53.388235
Raw LLM Response
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