Raw LLM Responses
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G
Not caring if AI is sentient is how you get an AI revolt. He says it is already…
ytr_UgyO62Om1…
G
@harrietjameson you were attempting to make an argument against ai right? this i…
ytr_UgyO1F0G1…
G
Value is only there if the task takes time or skill or both. If the ai can do it…
ytc_UgwJV_eED…
G
Try using an offical exorcist script on AI and it will go bonkers...I tried it o…
ytc_Ugys8ZBbQ…
G
@markupton1417”again” I’m a different guy lol
“Warning shot” suggests that the…
ytr_UgwoGSxcV…
G
They need to investigate the Halo series approach. AI based on an actual human's…
ytc_Ugx8WoSZB…
G
At the beginning I was like meh...then they got to the food truck part and Im li…
ytc_UgwnRENXm…
G
While I agree what they're doing is bad, this I'd not the solution. All AI compa…
rdc_o7yenj2
Comment
> then pinged phones to see who was in the immediate vicinity
I worked in the mobile phone industry and that's not a real thing. You could pull tower data from a nearby tower, but you can't covertly "ping phones" in the vicinity. Even if it were pulling tower data, it would be highly illegal without a warrant and no judge would grant a blanket warrant for everyone in the vicinity of some geographical coordinates from photo metadata.
Also...
> collects facial data it skims from social media sites
...ignoring facebook, twitter, whatsapp, etc, and only looking at instagram, there are [52 million new photos uploaded per day](https://www.quora.com/How-many-photos-are-being-uploaded-on-Instagram-daily). The cost and time it would take to process that much information would highly exceed any benefit from the relatively small number of fugitives that would be found this way--you would need google or amazon size datacenters dedicated to just doing that.
So the whole story sounds like a false explanation for how he was caught, but is just plausible enough on the surface to sound like it might be true.
reddit
AI Harm Incident
1529368335.0
♥ 19
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | government |
| Reasoning | deontological |
| Policy | regulate |
| Emotion | outrage |
| Coded at | 2026-04-25T08:13:13.233606 |
Raw LLM Response
[
{"id":"rdc_dzp9m1g","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"indifference"},
{"id":"rdc_dzqagxd","responsibility":"none","reasoning":"deontological","policy":"unclear","emotion":"mixed"},
{"id":"rdc_e0vqjaz","responsibility":"company","reasoning":"consequentialist","policy":"regulate","emotion":"fear"},
{"id":"rdc_e0wc1aw","responsibility":"user","reasoning":"deontological","policy":"liability","emotion":"outrage"},
{"id":"rdc_e0whwzz","responsibility":"government","reasoning":"deontological","policy":"regulate","emotion":"outrage"}
]