AI-सामग्र्यधिकाराः
What AI systems may do with content: read, summarize, transform, retrieve, train, commercialize, redistribute. The AICR ruleset and the AICL-C content-licensing layer make these rights declarable and transactable.
अध्ययनाधीनाः प्रश्नाः
01
robots.txt तः परं प्रति-उपयोगं प्रति-गभीरतां च सामग्री-अनुमतयः
02
श्रेयनिर्देशः, उद्धरण-सीमाः, धारण-नियमाश्च
03
प्रशिक्षण-वाणिज्यिक-उपयोगयोः सुरक्षणानि
04
अनुज्ञापन-प्रवाहाः, अनुज्ञा-token-चिह्नानि, परीक्षापञ्जिकाः च
सम्बद्धानि श्वेतपत्राणि
- AICR / AICL as an AI Content Licensing and Agentic Payment Connection Layer AI-सामग्र्यधिकाराणां अनुज्ञापन-कार्यप्रवाहानां च घोषणार्थं यन्त्रपाठ्यः विनिर्देश-स्तरः — AI-crawling सामग्र्यधिकारेभ्यः यन्त्र-व्यवहारक्षम-ज्ञान-जालं यावत्।
- 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 राजनैतिक-अर्थशास्त्रीयः तर्कः: सहस्रकोटि-स्तरीयानि AI-मूल्यांकनानि स्तरीकृत-सामग्री-अनुज्ञापनस्य सार्वजनिक-लाभ-विभाजनस्य च कृते वैधता-दबावं जनयन्ति — दत्तांशः स्तरीकृतः भवति, न तु महार्घः।
- 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.
- 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.