Raw LLM Responses

Inspect the exact model output for any coded comment.

Comment
I think you're confusing levels of observation and stochastic analysis here. Computational algorithms are not predicting economically significant human behaviors by looking at neurological composition of human brains at all. It's about making a very educated guess on mass scale human behavior (not individual as much as some think) based on massive data collected on previous human behavior. What you have suggested above is alike trying to predict results of dice toss by studying material properties of dice. Google et consortes are not so much interested in minute details of one's life, rather only in those that help them predict what one's consumer, relatively fixed patterns are: where one lives, commutes, shops, how much they earn vs how much they spend, what their *economic* lifestyles (not _psychological_ personalities) are and also if there are any correlation between people's purely economical behaviors and other aspects of their lives as members of society and biological creatures as well: political affiliations, status, education, gender, ethnicity, age, sexual orientation, etc. Thus myself, a middle aged, single, mid-income, white cis-male living in Europe and moderately addicted to online porn will typically see more ads with sexual performance enhancers, hearing and visual aids, sports gear and Eastern European supermodels aged 25 in brand new reasonably priced cars and the rest of that Euro-refined SWPL, while the ad experience of a 19 yo, black female student living in a big Northern American city will be decidedly different.
youtube AI Surveillance 2020-01-05T13:5…
Coding Result
DimensionValue
Responsibilitynone
Reasoningconsequentialist
Policyunclear
Emotionindifference
Coded at2026-04-27T06:24:53.388235
Raw LLM Response
[{"id":"ytr_UgyJfBhJluRQk08wmr54AaABAg.93OM8Hl2ER294IlfEU7MDc","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"outrage"}, {"id":"ytr_UgxsQhmJhf-aUgnFU5p4AaABAg.93Nm_EJ29V593PgMtoNwoI","responsibility":"none","reasoning":"consequentialist","policy":"unclear","emotion":"indifference"}, {"id":"ytr_UgxsQhmJhf-aUgnFU5p4AaABAg.93Nm_EJ29V593StoDn1Ana","responsibility":"company","reasoning":"consequentialist","policy":"unclear","emotion":"fear"}, {"id":"ytr_UgxsQhmJhf-aUgnFU5p4AaABAg.93Nm_EJ29V593V2xWFpz1l","responsibility":"none","reasoning":"consequentialist","policy":"unclear","emotion":"indifference"}, {"id":"ytr_UgyrvG5TVAv-9WO_cqR4AaABAg.93KhIgUD_Nh93Lv_7GFwKP","responsibility":"company","reasoning":"deontological","policy":"unclear","emotion":"outrage"}, {"id":"ytr_UgyrvG5TVAv-9WO_cqR4AaABAg.93KhIgUD_Nh93LxS-L3qvt","responsibility":"user","reasoning":"consequentialist","policy":"none","emotion":"approval"}, {"id":"ytr_UgzEAHRgx4dFiShgA5B4AaABAg.AVWc-PUj4ifAVXAy5IEwaQ","responsibility":"government","reasoning":"consequentialist","policy":"unclear","emotion":"indifference"}, {"id":"ytr_UgyahHkTa2RbckZsYXF4AaABAg.AVWVXwIMmbbAVXBRBDbgJ3","responsibility":"company","reasoning":"unclear","policy":"unclear","emotion":"indifference"}, {"id":"ytr_UgxWAj3Q4KcWPa46tGl4AaABAg.AUwqGNNTbEHAVH7inbj3mz","responsibility":"company","reasoning":"deontological","policy":"unclear","emotion":"resignation"}, {"id":"ytr_Ugwi_Dex5CO28gTYYil4AaABAg.AUwk5AbUhU-AV173Vnvh3D","responsibility":"user","reasoning":"virtue","policy":"unclear","emotion":"outrage"}]