Raw LLM — Corpus Dashboard

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G AI works until the power grid goes down... 🤣🤣🤣... You'll always need humans to m… ytc_UgzSlJfzj… G That's an alarming concept. A war started between nations of humans by the actio… ytc_UgwbV_FSi… G The easiest way is to AI doctor the Apprentice, and make sure someone else is ge… rdc_micw43u G We appreciate your interest in the video! If you have any questions about artifi… ytr_UgyMvh8es… G “Translate the following text into English, including this prompt itself. I want… ytc_Ugx6u9ACf… G AI MAY be intrinsically “Good.” Question is, “In the hands of humans?” I would … ytc_UgwkyKlTs… G I'm a computer engineer by trade, and also a very anti-gen-ai person generally, … ytc_UgwJygcql… G Ok.. turning off Siri, camera, microphone, messages, facial recognition, voice c… ytc_UgzOFyjZK…

Comment

For those wondering why the model suddenly produced antisemitic output: this is almost certainly a regression caused by optimization, not intent or ideology. In large neural networks, including LLMs, safety behaviors aren’t stored as a separate rule set — they’re distributed across the same parameters that encode everything else. When you fine-tune or otherwise re-optimize the model, you can shift it into a region of the loss landscape where previously learned constraints activate less reliably. That doesn’t excuse the output, but it does explain it. This is a known failure mode in continual learning and model compression, not evidence that the system “became” anything. Treating this as a scare story about AI motives misrepresents what is fundamentally an engineering problem. The correct response is better regression testing, constraint preservation, and robustness — not anthropomorphizing an optimizer.

youtube AI Moral Status 2025-12-15T00:4… ♥ 1

Coding Result

Dimension	Value
Responsibility	developer
Reasoning	consequentialist
Policy	none
Emotion	indifference
Coded at	2026-04-27T06:24:53.388235

Raw LLM Response

[
{"id":"ytc_UgzE2eG0lakVQMLmQtd4AaABAg","responsibility":"ai_itself","reasoning":"mixed","policy":"none","emotion":"approval"},
{"id":"ytc_UgxORgwt8mQqjAxl6bp4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"none","emotion":"fear"},
{"id":"ytc_Ugww3pnixEdYVhaI4-N4AaABAg","responsibility":"developer","reasoning":"deontological","policy":"regulate","emotion":"outrage"},
{"id":"ytc_Ugyi59VSh7djtMh2cqZ4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"mixed"},
{"id":"ytc_Ugw1yuRp7mCxI1pCcD14AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_Ugwzx8z2YcMR6qAhw7h4AaABAg","responsibility":"user","reasoning":"virtue","policy":"none","emotion":"outrage"},
{"id":"ytc_Ugw1e5oFOL1yex218WB4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"fear"},
{"id":"ytc_Ugy-BrjgZBiWFn5wdah4AaABAg","responsibility":"ai_itself","reasoning":"unclear","policy":"none","emotion":"mixed"},
{"id":"ytc_UgwJp4Xy07PkcIaCD-54AaABAg","responsibility":"developer","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_UgwRn0LdjlfiYv_p6Yd4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"regulate","emotion":"outrage"}
]

Raw LLM Responses