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G "I'm sorry" is often used as a phatic expression. It doesn't always _literally_ … ytc_UgwApFYOm… G As a tradesman if I knew there was a site with robort bricklayers local. in the … ytc_UgwkFG--b… G Have you tried the latest models like opus 4.6? I have been using it and it’s c… ytc_Ugy5CcRvw… G We need laws limiting companies who implement AI from cutting human employees, o… ytc_UgxVAAmnO… G I know this is probably not it but the whole video it felt like you promote this… ytc_UgxfcZgj8… G I think you are extremely naive if you think facial recognition is not already h… ytc_Ugxq23ShT… G The only reason this is at all feasible is because a consumer driven capitalist … ytc_UgxF9r7ei… G This is the coup-leader from Open AI. She and her Effective Altruism cronies are… ytc_UgxxfTVjR…

Comment

I think that, for some reason, wherever you guys say "trillion" you mean "billion". English uses the short scale mostly, where trillon is 10^12 and billion is 10^9. In the long scale a trillion is 10^18, so that's even less likely. Also, I think it would be good if Washington DC watched podcasts like this, but I doubt they do. I think the problem is time. There is so much knowledge, points of view, research to consume and understand, especially around difficult topics like AI, that most people, politicians included, simply don't have the time in the day to do it. We're dealing with a problem where human time and brain bandwidth are the bottleneck. Would lawmakers make better, more informed decisions if they spent several dozen or hundred hours doing their own research about the topic of AI that they're regulating? Most likely. Can they do it? Almost certainly not. Maybe their advisors can. Do the advisors have the time and skill to pass that knowledge up to their principals adequately? Hopfully yes. Can they pass on in 10 minutes what they learned in a 100 hours? Doubtful.

youtube AI Moral Status 2025-11-09T12:3…

Coding Result

Dimension	Value
Responsibility	government
Reasoning	mixed
Policy	regulate
Emotion	mixed
Coded at	2026-04-26T23:09:12.988011

Raw LLM Response

[
{"id":"ytc_UgzCfgXOWqj_QckvzY14AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytc_Ugy1PcgxyRpO6yFePBd4AaABAg","responsibility":"government","reasoning":"mixed","policy":"regulate","emotion":"mixed"},
{"id":"ytc_UgysOsgfV69frC13hlN4AaABAg","responsibility":"ai_itself","reasoning":"virtue","policy":"none","emotion":"outrage"},
{"id":"ytc_Ugzwr_KSzvipseA0Au94AaABAg","responsibility":"developer","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_Ugyl9pZdZa4uSa23sUZ4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytc_UgwB_5LjgvmB9LLCc3d4AaABAg","responsibility":"developer","reasoning":"deontological","policy":"liability","emotion":"fear"},
{"id":"ytc_Ugy03wl9LdwnUgQDn0l4AaABAg","responsibility":"company","reasoning":"mixed","policy":"regulate","emotion":"outrage"},
{"id":"ytc_UgzURJ6yX_tzv56jRcV4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_UgyySM7JDt6YFvJjZd54AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"approval"},
{"id":"ytc_Ugz8jelfArGzHzPt87F4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"}
]

Raw LLM Responses