@techreport{reilly-aipref-compliance-00,
    number =    {draft-reilly-aipref-compliance-00},
    type =      {Internet-Draft},
    institution =   {Internet Engineering Task Force},
    publisher = {Internet Engineering Task Force},
    note =      {Work in Progress},
    url =       {https://datatracker.ietf.org/doc/draft-reilly-aipref-compliance/00/},
    author =    {Lawrence John Reilly Jr},
    title =     {{Verifiable Compliance Records for AI Usage Preferences}},
    pagetotal = 19,
    year =      2026,
    month =     aug,
    day =       1,
    abstract =  {Work in the AI Preferences (AIPREF) Working Group defines a vocabulary for expressing preferences about how digital assets may be used by automated processing systems, together with mechanisms for attaching those preferences to content. Neither component provides a way for a processing entity to demonstrate that it observed an expressed preference, nor for a publisher or auditor to verify such a demonstration after the fact. This document defines the AI Usage Compliance Record (AUCR), a structure that binds a retrieved asset, the preference expression in force at the moment of retrieval, and the usage category the processing entity assigned to that asset. It defines an aggregation scheme that allows a processing entity to attest to very large numbers of records with a single signature, a proof mechanism that allows an individual publisher to audit only the records concerning its own assets, and a discovery mechanism for locating attestations and verification keys. The mechanism is deliberately confined to evidence: it makes claims of compliance falsifiable and non- repudiable, and takes no position on the legal effect of any preference or any record.},
}