Raw LLM Responses
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G
As much as I feel everything they did is wrong . It would be a fairly effective …
ytc_Ugyo9anwX…
G
That's the best use case for AI and essentially what it was made for - help huma…
ytr_UgzmwhroM…
G
Its funny because the one of the man and his daughter wouldn’t have an ai made i…
ytc_UgxZ8lSXE…
G
Suspect most of those hypothetical 'agent misalignment' situations purported by …
ytc_Ugy2sFO9g…
G
The simulation theory is so flawed it's not funny. I'm getting really over ai co…
ytc_UgzvTIt7I…
G
The first and second clip are both ai. The first one is just so super hyper real…
ytc_UgyGM6mHO…
G
Last year I started realizing we are no longer the decision maker concerning man…
ytc_UgzbcmFIj…
G
@Ivanprogamer30 I know AI can produce copyrighted characters. I don't believe i…
ytr_UgyWpbDm_…
Comment
Our current approach for AI will never be appropriate for engineering. LLMs are bullshit generators. They are only designed to produce a response that sounds like a person made it. They have no concept of truth or understanding.
At best LLM AI would produce results that sounded credible. This is a terrible thing for engineering. You need results that make logical sense and have been thought through, not results that “sound” right. There is already a big problem of humans copying engineering work and misapplying it to situations where it doesn’t apply, and humans are capable of knowing better. AI based on language models can’t do this as it has no way to know what is right or wrong.
That’s not to say people won’t use AI for engineering. Just that they shouldn’t, nor should anyone trust the work of such a program. It would be like taking away the library of conversations the LLMs use to fake being cognizant and expecting it to converse based on an understanding of the meaning of the actual words. The AI doesn’t understand words and it never did, that’s not how it works.
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Coding Result
| Dimension | Value |
|---|---|
| Responsibility | company |
| Reasoning | deontological |
| Policy | ban |
| Emotion | outrage |
| Coded at | 2026-04-25T08:33:43.502452 |
Raw LLM Response
[
{"id":"rdc_m293zbq","responsibility":"company","reasoning":"consequentialist","policy":"liability","emotion":"indifference"},
{"id":"rdc_m27rpuu","responsibility":"company","reasoning":"deontological","policy":"ban","emotion":"outrage"},
{"id":"rdc_m28iqcm","responsibility":"company","reasoning":"consequentialist","policy":"regulate","emotion":"outrage"},
{"id":"rdc_m29gd0g","responsibility":"distributed","reasoning":"consequentialist","policy":"none","emotion":"resignation"},
{"id":"rdc_m26nel0","responsibility":"unclear","reasoning":"mixed","policy":"unclear","emotion":"mixed"}
]