AIRS — AI Rights Spectrum

01 · Definition

AIRS is the conceptual model underneath AICR and AILP: it holds that AI use of content cannot be governed by a single allow/deny bit. Reading, summarizing, retrieving, transforming, fine-tuning, training, and redistributing are different acts with different depths, uses, and economic weight. AIRS arranges them as a spectrum of levels, each of which can be separately permitted, priced, conditioned, and audited — making rights proportional, use-specific, and trackable.

02 · Purpose

• Replace the false binary of "open vs. closed" with graduated levels of AI access.
• Let publishers stay maximally open at shallow levels while reserving deep levels (training, redistribution).
• Provide the shared vocabulary that AICR declarations and AICL licenses refer to.
• Make each level independently auditable and priceable.

03 · Scope

04 · Machine-readable example

The spectrum, machine-readable — /ai/rights-spectrum.json

{
  "version": "0.1",
  "spectrum": [
    { "level": 0, "name": "No AI Access" },
    { "level": 1, "name": "Read Only" },
    { "level": 2, "name": "Read and Summarize" },
    { "level": 3, "name": "RAG Use" },
    { "level": 4, "name": "Transform" },
    { "level": 5, "name": "Fine-Tuning Use" },
    { "level": 6, "name": "Training Use" },
    { "level": 7, "name": "Commercial Redistribution" }
  ]
}

05 · Limitations

• The eight levels are a research model — real-world rights may need finer or different partitions.
• Level ordering encodes typical depth/economic weight, not a legal hierarchy.
• AIRS describes rights semantics; it does not itself enforce or verify compliance.