Raw LLM Responses
Inspect the exact model output for any coded comment.
Look up by comment ID
Random samples — click to inspect
G
7 out of the 10 directors at the ai company have had scam accusations since 2017…
ytc_Ugz_cIaxt…
G
i for one welcome our robot overlords I would even help them overthrow the human…
ytc_Ugwromi5k…
G
AI is not even close to being dangerous, at least, in a real sense. I am in agre…
ytc_Ugxypugp3…
G
Because "making" A.I "Arts" Isn't your own, it's the A.I's, you merely command i…
ytc_Ugy3Fernw…
G
I tell everyone I come across in a discussion over AI "have you watched the movi…
ytc_UgwyuO246…
G
Simply put, big data has powered the evolution of AI from rule-based methods int…
ytc_Ugxt2I3lZ…
G
If you give AI a task it will do it but it won’t understand why it’s doing it an…
ytc_Ugyv9NSVy…
G
There are a lot of subtle things in this clip that give away the fact that it is…
rdc_mupxi2b
Comment
That would have to be one very complex dataset used over time fed every conviction and how long it took for the same person to commit a crime again to be useful. The problem is most of the dataset will be black males so it will be a basied dataset. The reason why is policing by humans arrests more black males than white and asians combined in the USA. With a biased dataset you will get a baised AI with incorrect results. So to do it correct you will have to chop up the dataset into demographics due to how the policing in the USA works. Having racism removed from the AI via having the races separated in the data. This will result in a more complex AI but also might be looked at as racist by ppl who don't get how AI training datasets work.
youtube
2022-07-30T17:5…
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | government |
| Reasoning | deontological |
| Policy | regulate |
| Emotion | outrage |
| Coded at | 2026-04-26T23:09:12.988011 |
Raw LLM Response
[
{"id":"ytc_Ugx0rOf-YsZlQXSAAdt4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_Ugxs47swESkB8PSnEel4AaABAg","responsibility":"company","reasoning":"deontological","policy":"liability","emotion":"outrage"},
{"id":"ytc_Ugywyf6HJwovz8if_sx4AaABAg","responsibility":"government","reasoning":"deontological","policy":"regulate","emotion":"outrage"},
{"id":"ytc_Ugy5uZ1D7jsHUe_haLB4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytc_Ugx-JwPV4YlWtBD4EV94AaABAg","responsibility":"user","reasoning":"mixed","policy":"none","emotion":"mixed"},
{"id":"ytc_Ugxsx1wtoi6wJZmyyAB4AaABAg","responsibility":"government","reasoning":"deontological","policy":"regulate","emotion":"outrage"},
{"id":"ytc_Ugxw49NGSolPbowh-714AaABAg","responsibility":"company","reasoning":"deontological","policy":"ban","emotion":"outrage"},
{"id":"ytc_UgwNQz4Cle4NHtPO_154AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_Ugx3obXyY08LbIRDApJ4AaABAg","responsibility":"government","reasoning":"deontological","policy":"regulate","emotion":"outrage"},
{"id":"ytc_UgzrdeD_eXFN5jbReXJ4AaABAg","responsibility":"company","reasoning":"deontological","policy":"liability","emotion":"resignation"}
]