AI Content Rights
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.
Questions under study
01
Per-use, per-depth content permissions beyond robots.txt
02
Attribution, excerpt limits, and retention rules
03
Training and commercial-use reservations
04
Licensing flows, license tokens, audit logs
Related whitepapers
- AICR / AICL as an AI Content Licensing and Agentic Payment Connection Layer A machine-readable specification layer for declaring AI content rights and licensing workflows — from AI crawling and content rights to a machine-transactable knowledge web.
- 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 A political-economy argument: trillion-scale AI valuations create legitimacy pressure for tiered content licensing and public benefit-sharing — data becomes tiered, not expensive.
- 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.