Raw LLM Responses

Inspect the exact model output for any coded comment.

Comment
The challenge is to eliminate unfounded bias while retaining the data-driven differences that impact the diagnosis and treatment. This is THE problem with AI: LLMs are just collating and echoing human words and data with very limited validation. So historical human prejudice is treated the same as peer reviewed data analysis. The only solution we have so far is to have humans validate the AI training set, and that would be an insanely long and expensive process.
youtube AI Bias 2025-11-08T16:3…
Coding Result
DimensionValue
Responsibilityai_itself
Reasoningconsequentialist
Policynone
Emotionmixed
Coded at2026-04-26T23:09:12.988011
Raw LLM Response
[ {"id":"ytc_UgzQV84-T56PikTkEPR4AaABAg","responsibility":"distributed","reasoning":"consequentialist","policy":"none","emotion":"mixed"}, {"id":"ytc_UgwRtFy82TGAM7y8Bhh4AaABAg","responsibility":"developer","reasoning":"mixed","policy":"none","emotion":"outrage"}, {"id":"ytc_UgzctaOTgp044PHAtYx4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"mixed"}, {"id":"ytc_Ugwi2Qmc5hKsnKxZjW14AaABAg","responsibility":"developer","reasoning":"mixed","policy":"none","emotion":"resignation"}, {"id":"ytc_UgxdyVAOw1EmP4N6mOR4AaABAg","responsibility":"distributed","reasoning":"consequentialist","policy":"none","emotion":"mixed"}, {"id":"ytc_UgzbmTnwJR3Cmk7KixN4AaABAg","responsibility":"developer","reasoning":"mixed","policy":"none","emotion":"mixed"}, {"id":"ytc_UgwBoXLqIXJSG-ef_8p4AaABAg","responsibility":"company","reasoning":"mixed","policy":"none","emotion":"outrage"}, {"id":"ytc_UgzFvtsbrkXh-F9Z_Yl4AaABAg","responsibility":"distributed","reasoning":"consequentialist","policy":"none","emotion":"outrage"}, {"id":"ytc_Ugy7Y1C5CNTaELSOmHR4AaABAg","responsibility":"developer","reasoning":"mixed","policy":"none","emotion":"indifference"}, {"id":"ytc_Ugxy_1CKXbpMM0dFPj54AaABAg","responsibility":"developer","reasoning":"mixed","policy":"none","emotion":"mixed"} ]