Ruhusa ya Kujifunza ya IA
Kama IA inaweza kujifunza, kwa undani gani, kwa madhumuni gani, na chini ya wajibu gani. Kusomwa si sawa na kujifunzwa kutoka; «haijazuiliwa» si sawa na «inayojifunzika». AIRS na AILP zinabadilisha ruhusa ya kujifunza kuwa wigo wenye madaraja, unaosomwa na masini.
Maswali yanayochunguzwa
01
Undani wa kujifunza: uorodheshaji, embedding, kurekebisha kwa undani, mafunzo, distillation
02
Kwa nini uwazi usiotamkwa unaondolewa kutoka mitiririko ya mafunzo
03
Uwazi wa kiprotokoli: kufanya nia njema itekelezeke na masini
04
Miundo ya malipo iliyofungwa na undani wa kujifunza
Hati za utafiti zinazohusiana
- AI Rights Spectrum: From robots.txt to an AI Learning Permission Protocol AIRS na AILP zinaeleza ruhusa za kujifunza za IA kwa undani zaidi ya ruhusa/kataa ya aina mbili tu — kile IA inaweza kujifunza, kwa undani gani, kwa matumizi gani, chini ya malipo gani.
- Protocolized Openness: Why “Not Prohibited” Does Not Mean “Learnable” in the Age of AI Uwazi usiotamkwa unasomeka kama kutokuwa na uhakika wa kisheria kwa mitiririko ya IA na unaondolewa; ni ruhusa ya kiprotokoli, inayosomwa na masini pekee, inayofanya contenu ijifunzwe kwa hakika.
- 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.