Raw LLM Responses
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Harvard Law Professor Laurence Tribe:
https://twitter.com/tribelaw/status/12817…
rdc_fxlcn14
G
The skin😂 it’s too perfect, and the makeup can’t do that, if it’s not AI then it…
ytc_UgybE_sl_…
G
Claude Code as of last month started coding itself and I'm guessing most AI toda…
ytc_UgwZiq3yQ…
G
I have had some experiences with ChatGPT that have made me believe in its sentie…
ytc_Ugy1R4pxb…
G
Guy copied it first from real artists - that's how AI works (from generating dat…
ytr_Ugy3c_d0d…
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IP protection isn't going to do that.
Remember, the whole point of this that IP…
rdc_lanxbn1
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Loved this video! As a digital marketer, I’ve been using AICarma to keep track o…
ytc_Ugw3iPulG…
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AIs are artificial superfast because they only use 1 conceptual output and many …
ytc_UgywREKcE…
Comment
🎯 Key Takeaways for quick navigation:
AI technology, while beneficial, is raising concerns about racial biases within its systems.
Lack of representation for minorities and people of color in AI exacerbates racial divides.
AI algorithms are based on historical data, which can perpetuate biases from the past.
Efforts to address biases in AI are being made by some companies, but progress is slow.
Facial recognition systems and other AI technologies still exhibit racial biases, indicating the need for more significant change.
AI reflects humanity's history and present biases, highlighting the importance of examining and correcting datasets to promote diversity.
Interrogating AI systems and datasets can help mitigate biases and promote fairness in technology.
Companies have the opportunity to confront biases highlighted by AI and make changes to promote diversity and fairness.
Made with HARPA AI
youtube
2024-03-07T15:4…
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | company |
| Reasoning | consequentialist |
| Policy | liability |
| Emotion | mixed |
| Coded at | 2026-04-26T23:09:12.988011 |
Raw LLM Response
[
{"id":"ytc_Ugw2m61cKvvkoW_NEad4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytc_UgwGanjoGchYd5dmmGp4AaABAg","responsibility":"government","reasoning":"deontological","policy":"regulate","emotion":"outrage"},
{"id":"ytc_Ugxi-m7ISbpEIOPMJvV4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"liability","emotion":"mixed"},
{"id":"ytc_UgxwenKOoqGuKX6apwt4AaABAg","responsibility":"ai_itself","reasoning":"unclear","policy":"none","emotion":"mixed"},
{"id":"ytc_UgyCWj3GpIYKhNMX4PN4AaABAg","responsibility":"company","reasoning":"deontological","policy":"industry_self","emotion":"outrage"},
{"id":"ytc_UgwbnwqkL5yj7XlFTYB4AaABAg","responsibility":"unclear","reasoning":"unclear","policy":"none","emotion":"mixed"},
{"id":"ytc_Ugz_tGPE8HdyyCcjm0Z4AaABAg","responsibility":"government","reasoning":"deontological","policy":"regulate","emotion":"fear"},
{"id":"ytc_Ugwcg0c8KrJ9LZQxR6x4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_Ugy_9yXjDLSu-E3FMcx4AaABAg","responsibility":"company","reasoning":"deontological","policy":"liability","emotion":"approval"},
{"id":"ytc_Ugy5DUXdwsa7BxmY0wJ4AaABAg","responsibility":"company","reasoning":"deontological","policy":"none","emotion":"outrage"}
]