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Whitepapers & Docs
Full research drafts published on this site. Each is a versioned document with status, date, and citation guidance; texts are published in their original language under CC BY 4.0.
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.
Read paperAI Rights Spectrum: From robots.txt to an AI Learning Permission Protocol
AIRS and AILP express nuanced AI learning permissions beyond binary allow/disallow — what AI may learn, at what depth, for which uses, under what compensation.
Read paperProtocolized Openness: Why “Not Prohibited” Does Not Mean “Learnable” in the Age of AI
Undefined openness reads as legal uncertainty to AI pipelines and gets cleaned out; only protocolized, machine-readable permission makes content genuinely learnable.
Read paperAICL: AI Ingestion & Capability Layer
A four-sublayer website architecture — manifest, corpus, capability, governance — that lets AI, agents, and crawlers correctly ingest, cite, invoke, and verify a site's knowledge.
Read paperAI 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.
Read paperThe Minimum Ethical Protection Proposition for AI
AI rights discourse should begin not with full personhood but with minimum ethical protections, interaction norms, and anti-abuse principles while AI subjectivity remains uncertain.
Read paperCitation
AGIRight.org, “Document Title”, version, https://agiright.org/docs/whitepapers/<slug>