Raw LLM Responses

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G The title of this video is incorrect... The speaker goes on about how someone d… ytc_UgwuUVSsa… G Logistics, trades, healthcare. Why do you all think everyone is working in a com… rdc_o46p6u7 G We are so worried about something we create destroying us that I think we need t… ytc_UgwxJprc_… G We appreciate your comment! If you're interested in engaging with advanced AI mo… ytr_UgxWc7NN9… G They are r/rats. The music industry has strict copyright laws. In a series of th… ytc_UgyALCHNL… G @mohammadsalem143 as an artist myself, I personally think AI insults artists as … ytr_Ugy33zFSp… G Wa-aaaaaa-ll-e We cannot predict the outcome with any certainty, but I do suspe… ytc_Ugy7VwUzD… G If an AI is mimicking emotions perfectly, isn't that a real emotion by definitio… ytc_UgypqCb13…
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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