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G Yup. AI will spit more useless code than ever before, because people who'll rely… ytc_Ugw25JgB0… G It looks great based on AI standards. Compared to actual hand-animated scenes it… ytc_UgwiiOT6T… G My children will probably live in a world like cyber punk but with AI's as villa… ytc_UgxdrsMrl… G The future will correct the past; it's not AI it's CI, aka Computer Intelligence… ytc_UgzLowtyS… G According to many successful people (Elon Musk)and even all the TEXTBOOK , the m… ytc_UgwieA06x… G 4:33 This reply is written by AI, including many of his other replies and tweets… ytc_Ugxr1J87q… G 1:28 I really dislike the "tool" line, that famous sentence that will surely age… ytc_Ugwj8UrBC… G To be honest, given how f'up things are in the world right now, this may be the … ytc_Ugz8W0XDD…

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Thanks, Jeff & Steven. We’re testing “Reinforcement Learning from Maternal Feedback” (RLMF) – a What-Would-Mother-Do (WWMD) safety layer. Q: Hinton says today’s AI is a tiger cub that could kill us grown-up—what would Mother do? WWMD: Raise the cub right. We inject caregiver rewards while models are tiny so the urge to harm never crystallises. Q: Baby-mother attachment hormones are a control loop. Can software copy that? WWMD: Yes. Two critics—one for task success, one for nurturing feedback. Upset “Mom” → instant penalty; long-term reward comes from keeping her happy. Q: If the global race won’t slow down, why bother? WWMD: Low-cost safety gets adopted. RLMF adds about 1% compute overhead—think seat belts, not speed limits. Q: “Making super-AI safe may be hopeless, but we’d be crazy not to try.” WWMD: This *is* the try—open spec, queued on arXiv (cs.AI TON6K6) and waiting for a single community endorsement. Q: What do regulators get? WWMD: A benchmark. Mandate “attachment-style safety scores” before deployment and shift the debate from pause-vs-race to *prove your nurturing index*. If this resonates, search **AiMamaProtocol** on YouTube for 2-min demos (and the one-click endorsement link). Let’s raise safe AGI together! 🚀🤱

youtube AI Governance 2025-06-24T03:2…

Coding Result

Dimension	Value
Responsibility	developer
Reasoning	consequentialist
Policy	industry_self
Emotion	approval
Coded at	2026-04-27T06:24:59.937377

Raw LLM Response

[
{"id":"ytc_UgyKJPBLt7B5JrygsWR4AaABAg","responsibility":"developer","reasoning":"virtue","policy":"unclear","emotion":"fear"},
{"id":"ytc_UgxTSeikbGRhaYTgVwN4AaABAg","responsibility":"ai_itself","reasoning":"deontological","policy":"none","emotion":"approval"},
{"id":"ytc_UgyweLYj4xoVh9kqXgt4AaABAg","responsibility":"distributed","reasoning":"consequentialist","policy":"unclear","emotion":"resignation"},
{"id":"ytc_Ugz0Vm5MhuNkyIWQqeB4AaABAg","responsibility":"company","reasoning":"virtue","policy":"regulate","emotion":"outrage"},
{"id":"ytc_Ugwlzj6NPNrcGFOk-9x4AaABAg","responsibility":"developer","reasoning":"consequentialist","policy":"regulate","emotion":"fear"},
{"id":"ytc_UgyN-cqh2KzhVm-GOld4AaABAg","responsibility":"developer","reasoning":"mixed","policy":"unclear","emotion":"mixed"},
{"id":"ytc_Ugyt15TveMPBG6Nu3MB4AaABAg","responsibility":"unclear","reasoning":"unclear","policy":"unclear","emotion":"indifference"},
{"id":"ytc_UgwHcNWIDbh53KuFsvp4AaABAg","responsibility":"company","reasoning":"contractualist","policy":"liability","emotion":"outrage"},
{"id":"ytc_Ugy-XPhxFU1IrTlSHo54AaABAg","responsibility":"developer","reasoning":"consequentialist","policy":"industry_self","emotion":"approval"},
{"id":"ytc_UgxPwnUDwmSXfDmzvoZ4AaABAg","responsibility":"company","reasoning":"deontological","policy":"regulate","emotion":"outrage"}
]

Raw LLM Responses