Raw LLM Responses
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if these curriculums are so great, then why are kids failing aptitude tests? 3 …
ytc_UgxbZ4Oqo…
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I don't really see the problem. Unless the AI is giving out specific names and d…
ytc_Ugw39F_aa…
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when dr roman yampolskiy said "people developing ai say they will use ai to mak…
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I used LLMs for my work. It's really bad. If u can be replaced my LLMs maybe u w…
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anti-christ was described as a picture of a human that talks, very much like an …
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Same guy who believe other countries pay tariffs. And used his own alter ego to …
rdc_o0mykn4
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I think the big thing about why it's different from an artist taking inspiration…
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When the AI purposely answered test questions incorrectly. The problem is that t…
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Comment
In order to effectively leverage AI at a high-efficiency level, it's essential to invest time in understanding AI and exploring ways to integrate it into your workflow. AI isn't something you can learn in just 5 minutes; rather, it necessitates studying various AI tools and gaining access to the ones that best align with your daily tasks and company requirements.
However, many companies expect their employees to learn AI during their free time without providing support for AI online courses. Furthermore, most businesses don't purchase high-efficiency AI tools that specifically cater to the company's needs. They probably don't even know the names of these tools / apps.
While using tools like ChatGPT to compose emails or gather data can be useful, it's important to remember that these basic tasks do not fully capitalize on AI's potential. High-level AI usage involves combining multiple AI tools, writing AI-automated processes, and achieving 100% accuracy in output.
To maximize AI efficiency, companies should consider offering training programs and support to help employees develop the skills necessary to implement AI effectively. With the right tools and knowledge, businesses can transform their operations and stay ahead of the competition in the fast-paced, ever-evolving world of AI.
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2025-11-05T15:1…
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | company |
| Reasoning | deontological |
| Policy | industry_self |
| Emotion | approval |
| Coded at | 2026-04-26T23:09:12.988011 |
Raw LLM Response
[
{"id":"ytc_Ugy5_1Y8_70L-hyOUCx4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"regulate","emotion":"outrage"},
{"id":"ytc_Ugw2BatxpnmqzXvIfql4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_UgyjOXd8DZczBPr4eGx4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"mixed"},
{"id":"ytc_Ugw5VbWjVmafHaW6N4B4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"regulate","emotion":"outrage"},
{"id":"ytc_UgxvTjVO-mQjYybn4F94AaABAg","responsibility":"distributed","reasoning":"mixed","policy":"unclear","emotion":"resignation"},
{"id":"ytc_UgwRHk7VJlLpiXioSkJ4AaABAg","responsibility":"company","reasoning":"deontological","policy":"industry_self","emotion":"approval"},
{"id":"ytc_Ugz_f2lPp21Ru7zaT1l4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"approval"},
{"id":"ytc_UgzqWtMlHGv3qeVEwZh4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"regulate","emotion":"fear"},
{"id":"ytc_UgyT766viLrvOmRg-s54AaABAg","responsibility":"company","reasoning":"deontological","policy":"none","emotion":"indifference"},
{"id":"ytc_UgxgY7hxSeo8FEOlqpt4AaABAg","responsibility":"company","reasoning":"virtue","policy":"liability","emotion":"outrage"}
]