| Internet-Draft | Training Preference Signal | October 2026 |
| Kelley | Expires 3 May 2027 | [Page] |
This document describes how a service operator binds usage preferences
(e.g., "no AI training") to paths by writing ordinary robots.txt
groups keyed by a per-purpose policy token in the User-Agent line.
It introduces no new directive names and no new grammar: the path
language, longest-match precedence, and group structure of robots.txt
are not changed.¶
This note is to be removed before publishing as an RFC.¶
Status information for this document may be found at https://datatracker.ietf.org/doc/draft-kelley-aipref-training-preference-signal/.¶
Discussion of this document takes place on the AI Preferences Working Group mailing list (mailto:ai-control@ietf.org), which is archived at https://mailarchive.ietf.org/arch/browse/ai-control/. Subscribe at https://www.ietf.org/mailman/listinfo/ai-control/.¶
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Copyright (c) 2026 IETF Trust and the persons identified as the document authors. All rights reserved.¶
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A service operator binds usage preferences (e.g., "no AI training") to
paths by writing ordinary robots.txt groups keyed by a
per-purpose policy token in the User-Agent line.¶
User-Agent: __usage_ai-training Disallow: / Allow: /press-kit/
This expresses a preference against AI training for all paths
except those under /press-kit/, for which it expresses a preference
in favor (Section 4.2).¶
This document introduces no new directive names and no new grammar; the path language, longest-match precedence, and group structure defined by [ROBOTS] are not changed. As a result, the wide variety of existing parsers deployed across the Internet will continue to interpret traffic management signals as they did previously, and will ignore policy-token groups as they would any group for a user agent they do not recognize.¶
Path-specific bindings. Preferences can be expressed per path, and not only site-wide (Section 4.2).¶
Minimal distance from RFC 9309. Semantics, and ideally syntax, stay as close to [ROBOTS] as possible, so that authors and implementers can use the mental model they already have.¶
No large-scale duplication. robots.txt files are
size-constrained (Section 2.5 of [ROBOTS]), and some deployed
files already contain heavily duplicated groups. Expressing
preferences does not require restating existing rules
(Section 4.1).¶
Unchanged legacy behavior. A parser or consumer that does not implement this mechanism behaves as before. This holds for parsers that are actually deployed, not only for idealized RFC 9309 parsers. Conversely, implementations treat files that do not use this mechanism exactly as before (Section 4.2 and Section 4.3).¶
Consistent interpretation across consumers. This mechanism does not depend on the divergent parts of deployed parser behavior (Section 4.1).¶
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all capitals, as shown here.¶
An entity that operates an HTTP service, such as a website, and
publishes a robots.txt file for it. For preferences expressed
through this mechanism, the service operator is the "declaring
party" (Section 2 of [VOCAB]). [ROBOTS] calls this party a
"service owner".¶
An entity that interprets preference signals that a service operator expresses through the mechanism defined in this document.¶
In the sense of [ROBOTS]; software that parses robots.txt files
and matches product tokens and paths against their rules.¶
A product token (Section 2.2.1 of [ROBOTS]) whose RFC 9309 signals
a consumer uses to determine how content will be used. A policy
token need not appear in the User-Agent header field
(Section 10.1.5 of [HTTP]) of any outbound request. This document
introduces a new, cross-vendor policy token (Section 4.1).¶
A policy token documented by a single consumer. Some service
operators already include these in their robots.txt files.¶
The __usage_ai-training policy token corresponds to the definition
that the IETF aipref Working Group has arrived at
(Section 4.1 of [VOCAB]). The following definitions are quoted from
that document:¶
Using an asset to modify the learned parameters of a generative AI model.¶
The training of models that are used to perform exclusively non-generative tasks is not included in this category, even if the model is capable of generative tasks.¶
An AI model that is used to generate synthetic content in one or more modalities. Alternatively, an AI model that is made available for use to generate synthetic content in one or more modalities. This definition does not include a model that is used, or made available for use, for classification, ranking, or scoring, even where the model generates rationale for its output.¶
This document applies those definitions as follows:¶
The content retrieved from a path. The preferences that apply to an
asset are those expressed in the robots.txt file in effect when the
asset was retrieved (Section 2.4 of [ROBOTS]; see also [ATTACH]).¶
This document does not define a parallel vocabulary; it tracks the work of the aipref Working Group. Implementers SHOULD consider updating their definitions, and adding or removing vocabulary terms, as the aipref Working Group reaches consensus in additional areas.¶
This document defines the policy token __usage_ai-training.¶
The policy token conforms to the product-token syntax in
Section 2.2.1 of [ROBOTS] (letters, _, -).¶
Consumers MUST match policy tokens exactly, apart from case, as for
any product token. (Note that some deployed parsers match more
flexibly; the __ prefix makes accidental matches unlikely.)¶
A single group MAY name several policy tokens (consecutive
User-Agent lines; Section 2.2 of [ROBOTS]) to bind its rules to
several purposes. Policy tokens and other product tokens MAY be
mixed in a group.¶
To determine whether a preference has been expressed for a given path, a consumer looks up the path and policy-token combination as specified in Sections 2.2.1 and 2.2.2 of [ROBOTS].¶
However, wildcard groups (i.e., User-Agent: *) MUST NOT be interpreted
as matching the policy token.¶
If the lookup finds that the path is disallowed, a preference against the use described by the policy token has been expressed for that path. If it finds that the path is allowed, a preference in favor of that use has been expressed.¶
If no group contains the __usage_ai-training policy token (i.e.,
there is no User-Agent: __usage_ai-training line in the file), then
no preference has been expressed. If such a file contains a
proprietary policy token, consumers SHOULD interpret that token as
they would in the absence of this document, but MUST NOT treat it as
expressing a preference in the context of this document (see
Section 4.5).¶
Consumers MUST interpret the RFC 9309 signals being expressed based on
their own product token(s) exactly as they would in the absence of
this document. That is, ExampleBot still checks whether there are
rules for ExampleBot; if there are, they still express the service
operator's preference about crawling. Nothing in this document
changes that signaling.¶
Content-usage preferences and traffic management signals can both be
expressed in robots.txt, but they are independent and orthogonal.¶
This policy token is not a directive for crawling behavior.¶
A consumer MAY use preferences to inform crawling. For example, if it crawls only for purposes covered by the policy token, it MAY refrain from retrieving resources for which a preference against those purposes has been expressed.¶
If a service operator wishes to limit crawling, it MAY use groups for
crawlers' product tokens in robots.txt to do so.¶
Specific expressions SHOULD take precedence over general ones.¶
Consumers MAY document that they interpret rules that match
proprietary policy tokens as being more specific than the
__usage_ai-training policy token.¶
Private agreements MAY override preferences expressed via this mechanism.¶
The security considerations of Section 3 of [ROBOTS] apply to this mechanism.¶
This document does not introduce any new privacy considerations.¶
This document has no IANA actions.¶
The author is grateful to the Working Group's chairs, Mark Nottingham (Cloudflare) and Suresh Krishnan (Cisco), to the editors of the vocabulary draft, Martin Thomson (Mozilla) and Paul Keller (Open Future), and to the responsible Area Director, Mike Bishop (Akamai), whose incredible effort to facilitate discussion and endless patience (in addition to their own individual contributions) have made the Working Group's progress possible.¶
The author also thanks the following people for their substantial contributions to shaping the Working Group's discussion and for their partnership. Affiliations are listed for identification only, since IETF participants contribute as individuals.¶
| Name | Affiliation |
|---|---|
| Farzaneh Badiei | Digital Medusa |
| Lila Bailey | Internet Archive |
| Kevin Bankston | Center for Democracy and Technology |
| Fabrice Canel | Microsoft |
| Alissa Cooper | Knight-Georgetown Institute |
| Sonia Cooper | Microsoft |
| Glenn Deen | Comcast NBCUniversal |
| Caleb Donaldson | |
| Daniel Etcovitch | Anthropic |
| Christopher Flammang | Elsevier |
| Max Gendler | News Corp |
| Alex Gibson | News Corp |
| Jordan Gimbel | Microsoft |
| Mark Gray | OpenAI |
| Nate Hake | Travel Lemming |
| Gary Illyes | |
| Meredith Jacob | American University Washington College of Law |
| Mirja Kühlewind | Ericsson |
| Laurent Le Meur | EDRLab |
| Jo Levy | Norton Law |
| Greg Lindahl | Common Crawl Foundation |
| Krishna Madhavan | Microsoft |
| Sarah McKenna | Sequentum |
| Angela Mills Wade | European Publishers Council |
| John Mueller | |
| Chris Needham | BBC |
| Elaine Newton | Amazon Web Services |
| Victoria Noble | Electronic Frontier Foundation |
| Sebastian Posth | Liccium |
| Brendan Quinn | IPTC |
| Courtney Radsch | Open Markets Institute |
| Felix Reda | GitHub |
| Eric Rescorla | Independent |
| Matt Rogerson | Financial Times |
| Leah Romm | Cloudflare |
| Leonard Rosenthol | Adobe |
| Malikat Rufai | Meta |
| Achim Schlosser | Bertelsmann |
| Rony Shalit | Bright Data |
| Bradley Silver | Advance |
| Erin Simon | |
| Esther Tetruashvily | OpenAI |
| Michael Tremante | Cloudflare |
| Thom Vaughan | Common Crawl Foundation |
| James Whymark | Meta |
| Timid Robot Zehta | Creative Commons |
Many more people shaped the Working Group's discussion than appear above, and this list has almost certainly left out someone who belongs on it. Any such omission is inadvertent, and the author apologizes in advance.¶