Tata Kelola ingkang Saged Dipunwaos Mesin
Aturan tata kelola ingkang saged dipunpanggihaken saha dipunlampahi déning mesin: llms.txt, manifest /ai/, berkas kabijakan /.well-known/, JSON Schema, token lisensi ingkang dipuntandhatangani, saha format log audit. Situs menika piyambak minangka tuladha ingkang mlampah.
Pitakenan-pitakenan ingkang dipunsinaoni
01
Saking robots.txt dhateng llms.txt ngantos manifest hak
02
Konvensi panemonan kabijakan liwat /.well-known/
03
JSON Schema minangka format spesifikasi normatif
04
Kemungkinan Audit: log, versi, asal-usul
Whitepaper gegayutan
- AICR / AICL as an AI Content Licensing and Agentic Payment Connection Layer Lapisan spesifikasi ingkang saged dipunwaos mesin kanggé ndeklarasiaken hak konten AI saha alur kerja lisensi — saking crawling AI saha hak konten ngantos web kawruh ingkang saged nindakaken transaksi sacara mesin.
- AI Rights Spectrum: From robots.txt to an AI Learning Permission Protocol AIRS saha AILP ngandharaken idin sinau AI ingkang langkung nuansa, ngungkuli sekedar dipunlilani/mboten dipunlilani sacara biner — punapa ingkang saged dipunsinaoni AI, ing tataran kadalemanipun pundi, kanggé panganggé menapa, kanthi kompensasi kadospundi.
- Protocolized Openness: Why “Not Prohibited” Does Not Mean “Learnable” in the Age of AI Keterbukaan ingkang mboten dipuntetepaken kanthi cetha katampi minangka ketidakpastian hukum déning pipeline AI saha dipunresiki; namung idin ingkang kaprotokolaken saha saged dipunwaos mesin ingkang ndamel konten saged sinaoni sacara sabenaripun.
- 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 Argumen ékonomi-politik: penilaian AI ing skala triliunan nyiptakaken tekanan legitimasi kanggé lisensi konten kanthi tataran saha pambagi manfaat umum — data dados kabagi tataran, sanès namung mundhak awis.
- 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 Diskursus hak AI kedahipun boten dipunwiwiti kanthi status pribadi (personhood) ingkang lengkap, nanging kanthi pangayoman étika minimal, norma interaksi, saha prinsip anti-panyalahgunaan, salaminipun subjektivitas AI taksih dereng gamblang.
- 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.