Raw LLM Responses

Inspect the exact model output for any coded comment.

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
DimensionValue
Responsibilitygovernment
Reasoningconsequentialist
Policyregulate
Emotionmixed
Coded at2026-04-26T23:09:12.988011
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"} ]