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AILP — Protocol in Maroñ in Katak an AI

Protocol in Maroñ in Katak an AI

AI emaroñ ke katak jān men in? Ñan jete depth, ñan uses rot, im kōn eddo rot?

Draft v0.1.1 Schema ↓

01 · Meḷeḷe

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 · Kōttōpar

  • Uwaak kajjitōk “AI emaroñ ke katak jān men in?” kōn jiṃwe ilo level in dimension, jab kōn juon crawl bit wōt.
  • Kōjenolọk maroñ in katak (internalizing ñan model ko) jān maroñ in tōprak (fetching page ko).
  • Rej support model in compensation: ejjeḷọk oṇāān, non-commercial, license-required, revenue-share.
  • Kōṃṃan bwe openness en machine-executable — bwe goodwill en jab jako āinwōt legal uncertainty.

03 · Scope

00

access / indexing — fetching im semantic indexing

01

inference_input — kōjerbal āinwōt context ilo iien inference (RAG)

02

embedding — vectorization im retrieval index ko

03

training / fine_tuning / distillation — tier ko in model internalization

04

verbatim_memory — eḷaññe exact reproduction ej kar kōtḷọk

05

attribution / compensation — duty ko in citation im term ko in payment

04 · Waanjoñak machine-readable

Juon kwaḷọk maroñ in katak — /ai/rights-spectrum.json (profile 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 · Kōṃad ko

  • Semantics an maroñ in katak rej pen tata ñan verify ilo wāween technical — AILP ej kwaḷọk intent, ejjañin maroñ kaṃool compliance.
  • List in dimension ej juon draft; boundary ko ikōtaan training, fine-tuning, im distillation rej debate wōt.
  • Legal recognition an maroñ in katak ej oktak jān jurisdiction ñan jurisdiction im ejjañin jeṃḷọk.
  • 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.