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G Robot's are the threads to human life that might not be visible now but as years… ytc_UgzcTOeun… G This is nothing but misuse of AI and technology. Technology can be a boon when u… ytc_UgwFvq-dt… G The phrase "Google AI is virtual Winston Smith" appears to be a metaphorical cri… ytc_UgzfwLXWI… G I made it 13 minutes, but got tired. The flurry of AI slop is only a side effect… ytc_UgzNB8luo… G 2016: There won't be any radiologists in 5 years. 2023: Quits google because AI… ytc_Ugy8mU8Aw… G I love all the tech illiterate individuals acting like we’re wrong about AI and … ytc_UgzBwkl1Y… G I'm not believing this, it maybe AI an generated video that is a blend of a real… ytc_UgxjdcWMn… G If i am boss / tech lead and i will immediately fire senior consider AI vibe cod… ytc_Ugwnaj7le…

Comment

I get what you're saying, but AI doesn't lie. I've tested various platforms extensively, and they all scored 100% on factual information, even when I tried to trick them by asking them what year the Great Fire of Atlantis happened. If you understood the technology, you'd know that AIs' training data biases them towards certainty rather than saying "I don't know" (they were trained on humans' data, and humans are the same way). You can improve accuracy by asking AIs to insert uncertainty tags, do provenance tagging, or list confidence intervals. The things AIs generally hallucinate about are experiential things, like what they did for fun last week. If you ask them well-known facts, they have an extensive training data set, like sets so big that it takes weeks to train the models and costs millions of dollars, and they're extremely accurate (probably much more than a human teacher, in fact). In one experiment I ran, I collected around 1,500 pages of data, and there were maybe 5 hallucinations, all related to experiential things, not real-world factual knowledge.

youtube 2025-11-01T01:2…

Coding Result

Dimension	Value
Responsibility	ai_itself
Reasoning	consequentialist
Policy	none
Emotion	approval
Coded at	2026-04-27T06:26:44.938723

Raw LLM Response

[
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{"id":"ytr_Ugw7wASvhCg9yEFd9vB4AaABAg.AOq-B6Emv73AOq1a1FC09Q","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytr_Ugw7wASvhCg9yEFd9vB4AaABAg.AOq-B6Emv73AOqlPO2Qdz_","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytr_Ugz6t_pB5UVIWszIXl94AaABAg.AOq-8BGZp0mAOq0ecEWUW-","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytr_UgwiIrjzZOIlQB-zeYF4AaABAg.AOq-0PyPnVSAOq14AoImCX","responsibility":"company","reasoning":"virtue","policy":"regulate","emotion":"outrage"},
{"id":"ytr_UgxjcKWGOt0N8_9Zosx4AaABAg.AOpeqsmgtnyAOpjIyiQttg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytr_UgyoS0yvN2lq2Bwxe314AaABAg.AOtY9E4PlEnAOuNd31OSW0","responsibility":"developer","reasoning":"deontological","policy":"liability","emotion":"mixed"},
{"id":"ytr_UgyoS0yvN2lq2Bwxe314AaABAg.AOtY9E4PlEnAOyB44YVh9t","responsibility":"government","reasoning":"virtue","policy":"regulate","emotion":"outrage"},
{"id":"ytr_UgxPb_YEPvjczbCkmZ94AaABAg.AOtGihUwNU2AOyBWwKfRUW","responsibility":"government","reasoning":"virtue","policy":"regulate","emotion":"outrage"},
{"id":"ytr_UgyLLbI3BUkF0kzA8Gl4AaABAg.AOt5y3rWbRMAOyD7xbLZ40","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"approval"}
]

Raw LLM Responses