Raw LLM Responses

Inspect the exact model output for any coded comment.

Comment
There are many mistakes in this video. Why do you racist against China or Russia? In fact, China will regulate the use of generative AI. In contrast, America is quite free. In the United States, courts have ruled that the use of copyright data for machine learning in Author’s Guild v. Google is fair use. You misunderstood the principle of destroying market value. It only applies if your product is duplicated or published or not enough transformative. The use of data to train AI does not destroy the market value of that data. Unless the information is made to sell for research purposes. You have to make a good separation between training the AI and using AI to generate something. It is difficult to pay actors to train the AI. But when using AI to create an image of an actor for a commercial purpose. That's when you have to pay money or get consent from the actor. Using actors' images to train AI Maybe just be to make a fun caricature. Training the AI is just creating an image generator. It is difficult for you to claim in the process of machine learning. But if you use this machine to create pirated images, you must obtain consent first. If you use training AI data, you must pay compensation to the copyright owner. Elon Musk will get rich and can solve the Twitter crisis right away. In the "using reference" part. You lack knowledge of the intelligence. Humans do not make strange images because human beings have learned for a long time and have knowledge in many areas. The AI learned how each picture and each text were related. ฺBut did not learn anything else like the ChatGPT can't solve an easy math equation. If a human being lacks knowledge or is still a child, he will create strange images like AI as well.
youtube 2023-02-11T05:4… ♥ 1
Coding Result
DimensionValue
Responsibilitygovernment
Reasoningdeontological
Policyregulate
Emotionoutrage
Coded at2026-04-26T23:09:12.988011
Raw LLM Response
[ {"id":"ytc_UgwRjH0pevx_iE0_UR54AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"resignation"}, {"id":"ytc_UgzVVevnYcNVPlegIP54AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"resignation"}, {"id":"ytc_UgxRjJ3XU_FqwP8TPnJ4AaABAg","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"mixed"}, {"id":"ytc_Ugyha6a5NdkEXVbCpgZ4AaABAg","responsibility":"ai_itself","reasoning":"deontological","policy":"liability","emotion":"outrage"}, {"id":"ytc_UgyYG39mxsEs7vYkBzp4AaABAg","responsibility":"user","reasoning":"virtue","policy":"industry_self","emotion":"approval"}, {"id":"ytc_UgzoccxOkMTwxWV61kN4AaABAg","responsibility":"distributed","reasoning":"consequentialist","policy":"none","emotion":"mixed"}, {"id":"ytc_Ugyud3xoptAAVdYipIN4AaABAg","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"resignation"}, {"id":"ytc_Ugx1wXr1v5h-MncHtSt4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"}, {"id":"ytc_UgwxvGwoClMlilpUHtl4AaABAg","responsibility":"government","reasoning":"deontological","policy":"regulate","emotion":"outrage"}, {"id":"ytc_UgwWrOFCIb7KkjbqVhp4AaABAg","responsibility":"ai_itself","reasoning":"virtue","policy":"unclear","emotion":"approval"} ]