Raw LLM Responses
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G
I just finished The Age Of AI, this book with this video has now made for a bowl…
ytc_UgzMWlu_W…
G
Holy shit this is brutal ^^ I'm hobbyist and yes I'm using AI to write 97% of m…
ytc_UgxE5nM8K…
G
I know about a truck driving accident where the driver trusted the gps that ther…
ytc_UgwP9qWtG…
G
I'm using words like "self-awareness" without actually understanding what they m…
ytc_UgyfRN3gL…
G
The cat is out of the bag, and there are many misconceptions on how the AI diffu…
ytc_Ugz3NtYNi…
G
I feel like ive seen this same robot for 10 years, and it's not gotten any bette…
ytc_UgwDcmewT…
G
Hahaha merging AI and robotics some of these people so loud too rich and real wr…
ytc_UgzXSe3W2…
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You guys have no idea how disruptive automation will be. At least the White Hous…
ytc_Ughc6Md3h…
Comment
Imagine the following: A neural network which selects memorable pictures out of a large set of pictures. This model is trained by user choosen "memorable moments" in existing photos. The data shows a bias towards a ethnicity when people are in the pictures.
Would you synthetically alter that dataset to remove that bias or would you accept the fact that this bias is there due to human statistically significant preference?
IMHO you should keep the dataset as it is as it´s just a representation of the reality and will ultimately deliver better predictions for the users.
youtube
AI Bias
2018-12-23T16:3…
♥ 5
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | distributed |
| Reasoning | consequentialist |
| Policy | unclear |
| Emotion | mixed |
| Coded at | 2026-04-27T06:24:53.388235 |
Raw LLM Response
[
{"id":"ytc_UgypjSLh_9QkbGM_4pZ4AaABAg","responsibility":"company","reasoning":"deontological","policy":"none","emotion":"outrage"},
{"id":"ytc_Ugy0Pb31HEV4qb0YI9N4AaABAg","responsibility":"company","reasoning":"deontological","policy":"none","emotion":"outrage"},
{"id":"ytc_Ugzs8J0VncSTZMwDNVN4AaABAg","responsibility":"company","reasoning":"deontological","policy":"none","emotion":"outrage"},
{"id":"ytc_UgwsgD241nI-aWtf9Gp4AaABAg","responsibility":"company","reasoning":"mixed","policy":"unclear","emotion":"mixed"},
{"id":"ytc_Ugzsjsnb_UmMVe6n8Rd4AaABAg","responsibility":"user","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_UgwbYjpwU0Lpu6NLrTB4AaABAg","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"indifference"},
{"id":"ytc_UgwVhs0ZtK8GOuOcRDl4AaABAg","responsibility":"distributed","reasoning":"consequentialist","policy":"unclear","emotion":"mixed"},
{"id":"ytc_Ugx6znuogH2jYuRPBWV4AaABAg","responsibility":"user","reasoning":"deontological","policy":"industry_self","emotion":"approval"},
{"id":"ytc_UgwwrGB0B9Wc_pj6IeV4AaABAg","responsibility":"distributed","reasoning":"mixed","policy":"unclear","emotion":"resignation"},
{"id":"ytc_UgwHqawJS_LRTPIV5wl4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"liability","emotion":"outrage"}
]