Raw LLM Responses
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G
The only caviat is if they could prove the llm can consciously act, react and sh…
rdc_o9cqsz7
G
AI should be have never be even introduce into social media. It discredits peop…
ytc_UgwZDZybx…
G
We all start off loving to learn. Over time, public school teaches you to hate l…
ytc_Ugwp9XmMN…
G
there should be a distinct difference between creating a sentient robot who can …
ytc_UgiH_BILS…
G
My son studies AI engineering and quantum computers, working on his PhD. I have …
ytc_Ugz_IpY96…
G
Honestly I can imagine a near future where I would trust more and prefer a robot…
ytr_UgwJ46WaA…
G
If an average dude can do this from his average computer, we can be certain that…
ytc_UgzK8UgUC…
G
All of thr fails are just idiotis rushing unfinished products to market. The pro…
ytc_UgylbRNFT…
Comment
Leveraging a Large Language Model (LLM) as a judicial reference point prior to generating output is a sound strategy. This involves deconstructing the primary query into sub-questions and then utilizing the LLM as a reference, supported by validated sources to substantiate the final output. Employing weighted scales to assign confidence scores to specific values further enhances the process. The primary challenge lies in the immediacy of output generation; however, a more favorable outcome can often be achieved by allowing for additional processing time. Maybe
youtube
AI Responsibility
2026-03-25T22:5…
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | none |
| Reasoning | deontological |
| Policy | none |
| Emotion | approval |
| Coded at | 2026-04-26T23:09:12.988011 |
Raw LLM Response
[{"id":"ytc_UgxtaMqm9Yhe0eOBEjd4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"regulate","emotion":"outrage"},
{"id":"ytc_UgxGcI8CwYwqDCHTHyx4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"approval"},
{"id":"ytc_UgwyP5kKXpSN84kV01J4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"unclear","emotion":"mixed"},
{"id":"ytc_UgxO9bipVDapxF8ea9V4AaABAg","responsibility":"none","reasoning":"deontological","policy":"none","emotion":"approval"},
{"id":"ytc_UgxU17sIruI8CaFjiUt4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_UgzXsQJnLzwmjsfHZZN4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"ban","emotion":"outrage"},
{"id":"ytc_UgyuB13aSvot8bg35XJ4AaABAg","responsibility":"distributed","reasoning":"consequentialist","policy":"unclear","emotion":"fear"},
{"id":"ytc_Ugy2FyvdhO1814mm5sJ4AaABAg","responsibility":"company","reasoning":"deontological","policy":"industry_self","emotion":"mixed"},
{"id":"ytc_UgwDaUutZXic3I6a1sh4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"approval"},
{"id":"ytc_UgyiPjnbf8O_PNRibI14AaABAg","responsibility":"company","reasoning":"virtue","policy":"regulate","emotion":"outrage"}]