Raw LLM Responses
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G
Humans are the weak link. Have 3 different AI's analyze the same data, without …
ytr_UgyUeFPx_…
G
This guy reaction to a 77 year old admonishing how he wishes he spent more time …
ytc_Ugw2w1PI5…
G
Funny, but for real some smart people find ways of dealing with unhelpful though…
ytc_UgyfTqpQZ…
G
I use AI to make fun of it, it's fun to see how bad it fails and also to keep no…
ytc_UgxgMRT08…
G
The first target of AI should be lawyers. Scan the legal code in, and let AI giv…
ytc_UgwIMaiNG…
G
If people raging from the average person all the way to investers that has billi…
ytc_UgwgHWHrf…
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The same tech that's behind LLMs and generative AI has lits of uses. Like Google…
ytc_Ugzph8EQw…
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493 - Bookmark it - it will be taught to kids by their AI teachers!…
ytc_Ugzp5yEUm…
Comment
Facial-recognition is supposed to be a tool to be used as a _first-pass_ to simplify the notification of issues for law-enforcement, it's not meant to be used as the be-all, end-all, otherwise we wouldn't have cops, we'd have computers and robots doing law-enforcement. Once cops get a notice about something, they're supposed to manually check it. As the video said, it must NOT be used as blind evidence, it can only be used to _facilitate_ ACTUAL POLICE WORK AND INVESTIGATION. ¬_¬ That said, automation tools aren't always good; ALPRs is a system whereby various cameras throughout the city (on cop cars, on red-lights, on buildings, etc.) automatically and indiscriminately scan _every_ license plate they see and automatically check for any "problems" to report to the nearest cop to run them down. The problem with this is that due to how the system and criminals work, it will almost always end up screwing over people with minor infractions like unpaid parking tickets rather than actual criminals like traffickers. 😒
youtube
AI Harm Incident
2021-04-29T15:0…
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | user |
| Reasoning | deontological |
| Policy | industry_self |
| Emotion | approval |
| Coded at | 2026-04-26T23:09:12.988011 |
Raw LLM Response
[
{"id":"ytc_UgyoQg5TcionW1_G8uh4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"outrage"},
{"id":"ytc_UgyQebD9NzVU-T7zHft4AaABAg","responsibility":"company","reasoning":"deontological","policy":"liability","emotion":"outrage"},
{"id":"ytc_UgyrcurS1z6eNhKl9zt4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"mixed"},
{"id":"ytc_Ugz_8uUXE0ns5uDNAnR4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"mixed"},
{"id":"ytc_UgxZ2gIpq5WgwXm8Ijp4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"fear"},
{"id":"ytc_UgzgJMcZtI0PN5TLS2t4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_UgxA6HokWzLEneS59LZ4AaABAg","responsibility":"user","reasoning":"deontological","policy":"industry_self","emotion":"approval"},
{"id":"ytc_Ugw9DmWwWGW9viyucTx4AaABAg","responsibility":"developer","reasoning":"virtue","policy":"liability","emotion":"outrage"},
{"id":"ytc_UgxpgtObXUEG1BdW1Z94AaABAg","responsibility":"company","reasoning":"deontological","policy":"regulate","emotion":"outrage"},
{"id":"ytc_UgyGlYgqv5zuPdClZGZ4AaABAg","responsibility":"government","reasoning":"deontological","policy":"liability","emotion":"outrage"}
]