Raw LLM Responses
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G
Lol, Bard and Chatgpt are a joke and really currently have no true function. The…
ytc_Ugy1EdtJy…
G
If given a job and sentience the robot should be programmed to like doing the jo…
ytc_Uggbivfnf…
G
There should be an international label mark in every thing where you have used A…
ytc_UgwBquGZr…
G
This only works if the basic income supplements full time employment, we needed …
ytc_UgyS_oxNV…
G
Why did they hallucinate? This is THE most time consuming frustrating aspect of …
ytc_Ugz-AE3EW…
G
Ya like I really trust our government with this new AI tech. Who and the hell th…
ytc_UgztG_q2d…
G
Theres a %50 chance the idiots running the world now will whipe us out. Ill take…
ytc_UgygYTnmT…
G
Crazy to say that they don’t want China’s AI to control the world. China, the co…
ytc_UgzlSrQsw…
Comment
Deep seek reply:(China)
How China, USA, and India see AI empowerment differently:
🇨🇳 China → AI as national infrastructure
🔹 State subsidies, compute vouchers, solo entrepreneur laws
🔹 Goal: Lower barriers → mass entrepreneurship
⚠️ Risk: Control inequality
🇺🇸 USA → AI as market tool
🔹 Venture capital, deregulation, APIs & SaaS models
🔹 Goal: Efficiency & disruption → high returns
⚠️ Risk: Wealth inequality
🇮🇳 India → AI as inclusion strategy
🔹 Digital public infrastructure, state-backed VC, "AI for Global South"
🔹 Goal: Empower informal sector (farmers, artisans, small traders)
⚠️ Risk: Dependency on foreign AI models.
Chatgpt reply:(USA)
🇨🇳 China: Government-led AI → focus on control, surveillance, and large-scale deployment
🇺🇸 USA: Company-led AI → focus on innovation, profit, and global tech leadership
🇮🇳 India: People-focused AI → focus on affordability, inclusion, and public digital systems like Aadhaar and Unified Payments Interface
👉 In one line:
China = control | USA = innovation | India = inclusion
Google gemini give conclusion:
Key Differentiation in AI Strategies
USA: Efficiency/Profit
China: Control/Mass Deployment
India: Inclusion/Public Sector Application
youtube
AI Jobs
2026-04-18T06:0…
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | government |
| Reasoning | consequentialist |
| Policy | regulate |
| Emotion | mixed |
| Coded at | 2026-04-26T23:09:12.988011 |
Raw LLM Response
[
{"id":"ytc_UgxAEU6lPXg6Djioj854AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"regulate","emotion":"approval"},
{"id":"ytc_UgzMGIwigll55WZIDKN4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytc_Ugw6ugvO3dfbnJbQsBh4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_UgwyDXLh6SkaOU7OcyB4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytc_UgytnYY-dL6RjExui1Z4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"mixed"},
{"id":"ytc_UgyLvXlnQQw9aCWgevJ4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"mixed"},
{"id":"ytc_UgxsJrKBoVTPEy7nbTZ4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"regulate","emotion":"outrage"},
{"id":"ytc_Ugyx8b7siAcAgVsmAs54AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"regulate","emotion":"mixed"},
{"id":"ytc_Ugy4EJskLu_fGYGo_hR4AaABAg","responsibility":"ai_itself","reasoning":"deontological","policy":"none","emotion":"indifference"},
{"id":"ytc_UgwZnhaaMrdAHfg45zV4AaABAg","responsibility":"government","reasoning":"consequentialist","policy":"regulate","emotion":"mixed"}
]