Raw LLM Responses

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G Hypothetical Discovery Timeline with Years + Spinoffs 2030–2035 → Riemann Hypot… ytc_UgyfLDe-p… G I've only really found 1 good use of AI quickly generating characters for TTRPGs… ytc_UgxQbxWPQ… G I’ve just started noticing all the literal AI copy voices of artists with covers… ytc_UgxMc4Vjo… G It’s ok to just call it suttle AI Propaganda. This analysis did have some good … ytc_Ugx5e4ITd… G So the Terminator movies werent make believe. They were in fact documentaries? 🤔… ytc_UgyXnbGU9… G they are going to connect the wrong wires then it will be a robot apocalypse 💯😂 … ytc_UgweGuWQO… G This is why laws must exist that someone must always be behind the wheel of the … ytc_UgxJb2AFE… G The funny thing is that those AI researchers could be rich beyond their wildest … ytc_UgzR101G9…
Comment
Facts: "Face recognition algorithms boast high classification accuracy (over 90%), but these outcomes are not universal. A growing body of research exposes divergent error rates across demographic groups, with the poorest accuracy consistently found in subjects who are female, Black, and 18-30 years old. In the landmark 2018 “Gender Shades” project, an intersectional approach was applied to appraise three gender classification algorithms, including those developed by IBM and Microsoft. Subjects were grouped into four categories: darker-skinned females, darker-skinned males, lighter-skinned females, and lighter-skinned males. All three algorithms performed the worst on darker-skinned females, with error rates up to 34% higher than for lighter-skinned males (Figure 1). Independent assessment by the National Institute of Standards and Technology (NIST) has confirmed these studies, finding that face recognition technologies across 189 algorithms are least accurate on women of color." ~ Harvard University
youtube AI Harm Incident 2023-08-14T12:1… ♥ 6
Coding Result
DimensionValue
Responsibilitynone
Reasoningconsequentialist
Policyunclear
Emotionindifference
Coded at2026-04-27T06:26:44.938723
Raw LLM Response
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