Fale Tohi
Ngaahi Tohi Hinehina & Tohi
Ko e ngaahi talotalo fakatotolo kakato kuo pulusi ʻi he saiti ko ʻeni. Ko e taki taha ko ha tohi kuo fakavēsoneʻi ʻoku ʻi ai hono tuʻunga, ʻaho, mo e fakahinohino lave; ʻoku pulusi ʻa e ngaahi tohi ʻi honau lea tefito ʻi lalo ʻi he CC BY 4.0.
AICR / AICL as an AI Content Licensing and Agentic Payment Connection Layer
Ko ha konga vaʻinga lava ke lau ʻe he masini ki hono fakahā ʻo e ngaahi totonu ʻo e fakamatala AI mo e ngaahi founga laiseni — mei he crawling ʻa e AI mo e totonu fakamatala ki ha ʻinitaneti ʻilo ʻoku lava ke fai ai ha fefakatauʻaki fakamasini.
Lau e TohiAI Rights Spectrum: From robots.txt to an AI Learning Permission Protocol
ʻOku fakahaaʻi ʻe he AIRS mo e AILP ʻa e ngaahi tuku ako AI ʻoku loloto ange ʻi he fili ʻe ua pē tuku/taʻofi — ko e meʻa ʻe lava ke ako ai ʻa e AI, ʻi he founga fē hono loloto, ki he hā ngaahi fakaʻaonga, mo ha totongi fē.
Lau e TohiProtocolized Openness: Why “Not Prohibited” Does Not Mean “Learnable” in the Age of AI
ʻOku lau ʻe he ngaahi hala AI ʻa e ʻatā taʻe fakapau ko ha taʻepau fakalao pea ʻoku fakamaʻa liʻaki; ko e tuku pē kuo fakapolokoloʻi mo lava ke lau ʻe he masini ʻoku ne fakahoko ai ʻa e fakamatala ke lava moʻoni ke ako mei ai.
Lau e TohiAICL-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.
Lau e TohiAI Content Payment and the Network Democratic Economy
Ko ha fakamatala fakaʻakonomika-fakapolitikale: ko e ngaahi mahuʻinga AI ʻoku fuʻu lahi ʻo aʻu ki he trillion ʻoku ne fakatupu ha lomilomi totonu ki he laiseni fakatuʻunga ʻo e fakamatala mo e vahevahe ʻo e lelei fakalūkufua — ʻoku tuʻunga ʻa e data, kae ʻikai ke fuʻu totongi lahi.
Lau e TohiFrom 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.
Lau e TohiAARS 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.
Lau e TohiAADP 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.
Lau e TohiAGIRight.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.
Lau e TohiThe Minimum Ethical Protection Proposition for AI
Ko e alea fekauʻaki mo e ngaahi totonu AI ʻoku totonu ke ʻoua ʻe kamata ʻi he tāutaha kakato, ka ʻi he ngaahi maluʻi fakaʻulungaanga kihiʻi, tuʻunga fefakatahaʻaki, mo e ngaahi tefitoʻi moʻoni taʻofi fakamālohi, lolotonga ʻoku kei taʻepau ʻa e ongo tāutaha ʻo e AI.
Lau e TohiARHG — 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.
Lau e TohiLave
AGIRight.org, “Hingoa Tohi”, vēsone, https://agiright.org/docs/whitepapers/<slug>