Vhupfumi ha Luvhaḓa lwa Demokrasi lwa AI

Vhupolitiki-vhupfumi ha AI na zwiṅwalwa: u lifha nga u crawlwa, mbuelo dza data, mbulungelo dza masheleni dza AI dza shango, midzia ya mbadelo ya vhavhumbi, mabindu a data o dzudzanywaho nga maga, na nḓila ine ndeme yo dzhiwaho kha ndivho ya khagala ya nga vhuyedzela kha vho i bveledzaho.

Mbudziso dzi khou guḓiwa

U dzhia data hu si na mbadelo u vhambedza na ndeme ya AI ya di-thiriyoni ya dolara

Khani khulwane ya bindu ḽa data ḽo dzudzanywaho nga maga: data i vha na maga, hu si u dura

U kovhelana mbuelo dza data ya khagala na mbuelo dza AI

Mabindu a data yo ṱolisiswaho na mulanga wa vhathu vhanzhi

Maṅwalo makhulu o tshimbidzanaho

AICR / AICL as an AI Content Licensing and Agentic Payment Connection Layer Muraḓo wa zwiṱaluli zwine mishini ya kona u zwi vhala u itela u ḓivhadza pfanelo dza zwiṅwalwa zwa AI na mishumo ya mulanga — u bva kha u tou tolwa nga AI na pfanelo dza zwiṅwalwa u swikela kha webu ya ndivho ine ya ita mbambadzo nga mishini.
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 Khani ya vhupolitiki-vhupfumi: ndeme ya AI ine ya swika kha di-thiriyoni i vhumba khakhathi ya u ṱoḓa uri zwiṅwalwa zwi laisenisiwe nga maga na uri mbuelo dzi kovhelane na tshitshavha — data i vha na maga, hu si u dura.
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.