<?xml version="1.0" encoding="UTF-8"?>
<reference anchor="I-D.reilly-aipref-compliance" target="https://datatracker.ietf.org/doc/html/draft-reilly-aipref-compliance-00">
   <front>
      <title>Verifiable Compliance Records for AI Usage Preferences</title>
      <author initials="L. J. R." surname="Reilly" fullname="Lawrence John Reilly Jr">
         <organization>Independent</organization>
      </author>
      <date month="August" day="1" year="2026" />
      <abstract>
	 <t>   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.

	 </t>
      </abstract>
   </front>
   <seriesInfo name="Internet-Draft" value="draft-reilly-aipref-compliance-00" />
   
</reference>
