Raw LLM Responses
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Sorry creepy comment was not for you it was for something i was watching accide…
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'What-if' they hit super intelligence? They won't, you can't define intelligence…
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This obviously extremely intelligent women exudes such tremendous poise, determi…
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The difference between a mentor and AI is that the mentor wants you to learn so …
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Im particularly excited to see what comes from news outlets loosing ad revenue, …
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As an AI Prompter and an actual digital artist I would never even consider tryin…
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@thewannabecritic7490@thewannabecritic7490 is not bursting; there are too many …
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Human agency is an important ingredient in the ascendancy of AI. WEALTHY & POWER…
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Comment
@anarchic_ramblings this isn't my area of expertise and I'm sure there's more advanced metrics but a basic way would be to see if the accuracy massively changes based on some aspect of the input
Eg if we're making facial recognition software and noticed that the model performed noticeably worse on people with glasses we would say it's biased against people with glasses, or if it did better on photos of people on a plain background we would say it's biased towards those people
The problem comes with determining whether bias is expected, there will always be things that help the model (having plain backgrounds as above for example) but things like skin colour, gender, etc, we would hope that the model's performance doesn't depend on these attributes, and so it's important to have a well balanced dataset (or use other techniques to reduce bias)
youtube
AI Bias
2023-04-08T07:0…
♥ 1
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | none |
| Reasoning | consequentialist |
| Policy | none |
| Emotion | indifference |
| Coded at | 2026-04-27T06:24:59.937377 |
Raw LLM Response
[
{"id":"ytr_Ugx9pr52cMYqpnfGpox4AaABAg.AEhdoqlxF_6AEhiThoRmNF","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"indifference"},
{"id":"ytr_UgwAGi-DZxb-RjfeKgl4AaABAg.AEyP2yI3nm-AEyYFptEqvb","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"mixed"},
{"id":"ytr_UgxuYQGJh9HsgeU-qfV4AaABAg.AEiRHPvqTPKAEitT9QuZUa","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"indifference"},
{"id":"ytr_UgxuYQGJh9HsgeU-qfV4AaABAg.AEiRHPvqTPKAEmwoapAB1V","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"indifference"},
{"id":"ytr_UgyrOvP2b1QZiGNycDx4AaABAg.AEhe6l3xMF8AEhxAuybHqH","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"indifference"},
{"id":"ytr_UgwFuSp2Tjf9tnyhyc54AaABAg.9oDaT8LAy9V9oEXvd5JD1T","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytr_Ugxl1z0nSy0EPAR3reF4AaABAg.8e0dzWlhAA58e0pwlAvLol","responsibility":"ai_itself","reasoning":"consequentialist","policy":"liability","emotion":"fear"},
{"id":"ytr_UgyFaGcDlUAxxa36KRd4AaABAg.AUkgUViu3jFAVGjbyKVjAN","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"outrage"},
{"id":"ytr_UgzqnC899m3Qzn6ke-B4AaABAg.AOjmdk2mBxVAOpUYrpfj7c","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"mixed"},
{"id":"ytr_UgzzQa1xngDoc5kaIEN4AaABAg.ABJ3h3oEiFmAB_3o0zxWsR","responsibility":"government","reasoning":"deontological","policy":"regulate","emotion":"outrage"}
]