Raw LLM Responses

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G @CautionaryTales3 I think this is why it has to say it's AI. If it seeks autonom… ytr_UgwXEv5zJ… G If AI is truly f*****g "intelligent", then it would have called 911 FIRST and gi… ytc_Ugx1Cy1Jf… G that might work on flat roads in the south, but, i will find it very amusing to … ytc_UgwdmBbOT… G This is something I haven't thought of until now. These art AI models are quite… ytc_UgzidaLKl… G At what point do all the unemployed people get together and burn down the compan… ytc_Ugxkr39zD… G If pursued... or self improving a.i. is implemented, and civilization does NOT E… ytc_UgwDaXD2t… G ​@JustJasnovdesigning amd building a system is more than just architecture. It i… ytr_UgxFcw6Oz… G Hey, CS engineer here, with a huge interest and respect for human art. Engineers… ytc_UgwNnfnzC…
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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