Mashinada oʻqiladigan boshqaruv
Mashinalar topa oladigan va amalga oshira oladigan boshqaruv qoidalari: llms.txt, /ai/ manifestlari, /.well-known/ siyosat fayllari, JSON sxemalari, imzolangan litsenziya tokenlari va audit jurnali formatlari. Ushbu sayt oʻzi ishlaydigan namunadir.
Oʻrganilayotgan savollar
01
robots.txt dan llms.txt gacha, undan huquqlar manifestlarigacha
02
/.well-known/ siyosatni aniqlash konventsiyalari
03
JSON Schema me'yoriy spetsifikatsiya formati sifatida
04
Audit qilinuvchanlik: jurnallar, versiyalar, kelib chiqish
Bogʻliq ilmiy hujjatlar
- AICR / AICL as an AI Content Licensing and Agentic Payment Connection Layer AI kontent huquqlari va litsenziyalash jarayonlarini eʼlon qilish uchun mashinada oʻqiladigan spetsifikatsiya qatlami — AI kraulingi va kontent huquqlaridan tortib, mashina orqali bitim tuzsa boʻladigan bilim vebigacha.
- AI Rights Spectrum: From robots.txt to an AI Learning Permission Protocol AIRS va AILP ikkilik ruxsat/taqiqdan tashqari, AI qanday oʻrganishi mumkinligini nozik tarzda ifodalaydi — AI nimani, qay darajada chuqur, qaysi maqsadlar uchun va qanday kompensatsiya asosida oʻrganishi mumkinligini.
- Protocolized Openness: Why “Not Prohibited” Does Not Mean “Learnable” in the Age of AI Aniqlanmagan ochiqlik AI quvur liniyalari uchun huquqiy noaniqlik sifatida oʻqiladi va tozalab tashlanadi; faqat protokollashtirilgan, mashinada oʻqiladigan ruxsatgina kontentni haqiqatan ham oʻrganish mumkin qiladi.
- AICL-I v0.2: AI Ingestion & Capability Layer A five-component website architecture — manifest, corpus, capability, runtime control, governance — that lets AI, agents, and crawlers correctly ingest, invoke, and verify a site's knowledge and capabilities within explicit content, action, and authority boundaries.
- AI Content Payment and the Network Democratic Economy Siyosiy-iqtisodiy dalil: trillion dollarlik AI baholari darajali kontent litsenziyalash va jamoat foydasini boʻlishish uchun legitimlik bosimini yaratadi — maʼlumot qimmatlashib emas, darajalanib boradi.
- From Crawler Rights to Agent Authority: Extending AGIRIGHT from Content Governance to Protocol-Native AI Agents The bridge paper for AGIRIGHT's Agent & Protocol Rights family: why content permission, action permission, delegated authority, and inspection rights must be four separately-evaluated axes, not one.
- AARS v0.1 — Agent Action Rights Spectrum The full protocol draft behind the AARS page: an A0–A7 human-readable spectrum, a machine-readable action vector, and rules for composition risk and capability amplification.
- AADP v0.1 — Agent Authority & Delegation Protocol The full protocol draft behind the AADP page: principal ≠ actor, delegation that can only narrow, and an inspection ceiling that bounds how much a verifier may demand.
- AGIRight.org Technical White Paper v0.2 — From AI Content Governance to Protocol-Native Agent & Authority Rights The site's current architecture document: six protocol drafts across two families (content & learning, agent & protocol rights), an integration layer, and an ethical-protection layer, plus the acceptance criteria this site update was built against.
- The Minimum Ethical Protection Proposition for AI AI huquqlari haqidagi muhokama toʻliq shaxslikdan emas, balki AI subʼyektivligi hali noaniq boʻlgan davrda minimal axloqiy himoya choralari, oʻzaro taʼsir normalari va suiisteʼmolga qarshi tamoyillardan boshlanishi kerak.
- ARHG — Agent-Readable Hyperlink Graph and Permissioned Web Control Plane A machine-readable navigation graph alongside the ordinary site, answering what AICR/AILP and AARS/AADP both assume: can this resource even be found, by whom, and where does it lead.