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AILP — Protocol da la Permissiun d'Emprender da la IA

Protocol da la Permissiun d'Emprender da la IA

Ha la IA lubientscha dad emprender da quai? En tge profundità, per tge diever, cun tge obligaziuns?

Draft v0.1.1 Schema ↓

01 · Definiziun

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 · Intent

  • Respunder a la dumonda «ha la IA lubientscha dad emprender da quai?» cun ina precisiun a nivel da dimensiuns, empè d'in simpel bit da crawling.
  • Separar la permissiun d'emprender (internalisar en models) da la permissiun d'access (retrair paginas).
  • Sustegnair models da retribuziun: gratuit, betg-commerzial, licenza necessaria, participaziun als retgavs.
  • Garantir che l'avertadad saja exequibla per maschinas — uschia che la buna voluntad na vegn betg eliminada sco incertitude giuridica.

03 · Champ d'applicaziun

00

access / indexing — retrair ed indexaziun semantica

01

inference_input — diever sco context al mument da l'inferenza (RAG)

02

embedding — vectorisaziun ed indexs da retrair

03

training / fine_tuning / distillation — nivels d'internalisaziun dal model

04

verbatim_memory — sche la reproducziun exacta è lubida

05

attribution / compensation — obligaziuns da citaziun e cundiziuns da pagament

04 · Exempel leschibel per maschinas

Ina decleraziun da permissiun d'emprender — /ai/rights-spectrum.json (profil 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 · Limitaziuns

  • La semantica da la permissiun d'emprender è la pli difficila da verifitgar tecnicamain — l'AILP declera l'intenziun, ma na po anc betg cumprovar la conformità.
  • La glista da dimensiuns è in project; ils cunfins tranter instrucziun, fine-tuning e distillaziun èn anc discutads.
  • La renconuschientscha giuridica da permissiuns d'emprender varia tenor la giurisdicziun e resta betg schliada.
  • 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.