Raw LLM Responses

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Comment
When it comes to attempting to draw links between correlated sets, it is critical to focus on what drives them apart from the sets that don't correlate or do it differently. When we find that most of the students who achieve better grades are also reporting using AI-powered tools, you have to wonder what high-achieving students would like to use AI for. Students who do well in class are likely to be highly motivated to either work or learn directly through learning itself. Such students are highly likely to be interested in tools that could help them manage their work better, as well as prepare for their tests more efficiently. While a cruising student who only wants to get passing grades so they get their degree would certainly be interested in tools that do the assignments for them, I could very must see a hard-working student being amazed at the idea of having an automated study-buddy to quizz you on the materials before the test. Also, you downright refused the argument that using an AI model to write an assignment was like sending a robot to the gym in your stead, but you made that exact point yourself around the 10 minute mark. Maybe you reacted in that obtuse way because you decided that he was strictly seeing no good from AI models based on that quote you mentionned, even though your interpretation of it is wrong. To state that one would be pleased to see that tech disappear doesn't mean that they see it strictly as a negative impact, but simply as a NET negative. I, myself, see plenty of positive applications from generative AI. Yet, it in comparison, it has had such a negative impact already that I would rather have it gone entirely.
youtube 2025-09-01T08:4…
Coding Result
DimensionValue
Responsibilitynone
Reasoningconsequentialist
Policynone
Emotionindifference
Coded at2026-04-27T06:26:44.938723
Raw LLM Response
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