Gxumela Kokuqukethwe
AGIRight.org

AILP — Iphrothokholo Yemvumo Yokufunda ye-AI

Iphrothokholo Yemvumo Yokufunda ye-AI

Ngabe i-AI ingafunda kilokhu na? Kubunjinini bani, ngasiphi isetjenziso, ngeembophi bani?

Draft v0.1.1 Isikhema ↓

01 · Incazelo

AILP operationalizes the AIRS spectrum for the specific question of learning. It distinguishes acts that binary crawler rules collapse together: being read is not being learned from; being retrieved is not being trained on; fine-tuning is not distillation; verbatim memorization is different from statistical internalization. AILP lets a publisher declare, in a single machine-readable file, per-dimension permissions — access, indexing, inference input, embedding, training, fine-tuning, distillation, memory, output, attribution and compensation — each as allowed, denied, or license-required. An AILP grant answers "may AI learn from this content?" only — it does not answer "may this Agent invoke a tool, write to a database, or publish?" (AARS), nor "who authorized this Agent?" (AADP).

02 · Umnqopho

  • Phendula umbuzo othi "ngabe i-AI ingafunda kilokhu na?" ngokunemba kwezinga lomlinganiso kunokusebenzisa ibhithi le-crawl.
  • Yehlukanisa imvumo yokufunda (ukungenisa ngaphakathi emamodelini) nemvumo yokufinyelela (ukulanda amakhasi).
  • Sekela amamodeli wesikhokhiso: mahala, angasi wokuthengiselana, adinga ilayisensi, wokwabelana ngenzuzo.
  • Qinisekisa bona ukuvuleka kuyasebenzeka yimitjhini — ukwenzela bona umoya omuhle ungalahlwa njengokungaqiniseki komthetho.

03 · Ibanga

00

access / indexing — ukulanda nokuhlelwa okunencazelo

01

inference_input — ukusetjenziswa njengesimo ngesikhathi sokucabangela (i-RAG)

02

embedding — ukwenziwa yi-vector nokuhlelwa kokulanda

03

training / fine_tuning / distillation — amazinga wokungeniswa ngaphakathi kwemodeli

04

verbatim_memory — ukobana ukukhiqizwa okunembileko kuvunyelwe na

05

attribution / compensation — imisebenzi yokucaphuna nemibandela yeenkhokhelo

04 · Isibonelo esifundeka yimitjhini

Isaziso semvumo yokufunda — /ai/rights-spectrum.json (iprofayela ye-AILP)

/ai/rights-spectrum.json
{
  "version": "0.1",
  "protocol": "AILP",
  "publisher": "example.org",
  "default": {
    "access": "allowed",
    "indexing": "allowed",
    "inference_input": "allowed",
    "embedding": "allowed",
    "training": "license_required",
    "fine_tuning": "license_required",
    "distillation": "denied",
    "verbatim_memory": "denied",
    "attribution": "required",
    "compensation": "contact"
  },
  "contact": "licensing@example.org"
}

05 · Imikhawulo

  • Iincazelo zemvumo yokufunda ngizo ezinzima khulu ukuziqinisekisa ngobuchwepheshe — i-AILP itjho ihloso, ayikakghoni ukufakazela ukuthotjelwa.
  • Uhlu lwemilinganiso lulidrafu; imikhawulo hlangana nokuqeqeshwa, ukulungiswa okunembileko, nokudistiliwa isesengcoceni.
  • Ukwamukelwa ngokomthetho kweemvumo zokufunda kuyahluka ngokwesigaba sezomthetho begodu akukaqedwa.
  • v0.1.1: AILP(Resource,ContentUse)=Allow does not imply AARS(Actor,Action)=Allow, and does not imply AADP(Principal,Actor,Authority)=Valid — a system exposing both content and tools must evaluate them separately.