Earlier today I wrote this one talking about AI Preferences Protocol and in that post I included this X post.
IETF (Internet Engineering Task Force) AI preferences working group recent meeting! The Youtube video of this meeting is really long over an hour but I was interested in knowing exactly what’s going on! and what will be coming out of this cuz almost every second day I’m getting asked about this issue by publishers (things like what we should do, should we block OpenAI or Google! we want to block Google from using content in AI Overviews but still show up in usual search results …………. a many other questions like this).
Anyway I used Gemini 2.5 Flash-Lite in Google’s AI Studio to do analysis of the transcript of this video. My full conversion with model in AI Studio can be accessed here. But below is the content from this video which might be interesting for SEO folks!
of course I used Gemini 2.5 Flash-Lite to curate the content below!
1. The Fundamental Concept of Signaling Preferences:
- 05:54 – 06:37: This section clearly states the purpose: “standardizing building blocks that allow for the expression of preferences about how content is collected and processed for artificial intelligence model development, deployment and use.” For an SEO consultant, this means understanding that websites will soon have a more structured way to communicate their desires regarding AI processing, which could influence how their content is treated beyond traditional search indexing.
2. The Role of robots.txt and HTTP Headers (Attachment Mechanisms):
- 01:01:22 – 01:04:05: This is a goldmine for SEO professionals.
- robots.txt as a preference signal: The discussion confirms that robots.txt is being used as a primary mechanism for attaching these preferences. SEOs already manage robots.txt for crawl control, so this extends its functionality.
- Time of acquisition vs. current state: The clarification that preferences apply at the “time of acquisition” is crucial. This means if a website owner updates their robots.txt or preference signals, it only affects newly acquired content, not content already processed under older rules. This has implications for how changes in preference signals propagate.
- “No preference is no preference”: This reinforces the importance of explicitly setting preferences if a site owner wants to control AI usage. If nothing is stated, the default might be different.
3. The Vocabulary and Categories of Use:
- 13:01 – 15:16: The proposed taxonomy of use cases like “Automated Processing,” “AI Training,” and “Generative AI” is vital.
- Impact on content indexing and ranking: While not directly about ranking factors, understanding these categories means SEOs can advise clients on how to signal preferences for different types of AI processing. For example, a client might want to disallow AI training but allow general automated processing for analytics.
- The “Search” carve-out: The specific inclusion and discussion of a “search” category (00:57:09.839 – 01:00:00.480) is extremely relevant. It clarifies that the intent is to allow explicit opt-outs for AI processing while still permitting traditional search engine crawling and indexing. This is critical for ensuring websites aren’t inadvertently blocking search engines when trying to manage AI usage.
4. The “Generative AI” vs. “Inference” Distinction:
- 27:11 – 37:22: The detailed discussion on narrowing the definition of “inference” and the split between generic inference and generative applications is important.
- How AI uses content: SEOs need to understand what types of AI processing are considered “inferential” or “generative” to advise clients on the most appropriate preference signals. This could impact how AI tools summarize or derive insights from content.
5. The “Overriding Preferences” and Exceptions:
- 19:44 – 23:20: The discussion about circumstances where preferences might be ignored (e.g., accessibility, legal exemptions, contracts) is relevant.
- Nuances of compliance: While robots.txt is a technical signal, it’s not always legally binding. SEOs need to understand these nuances to advise clients on the limitations of their preference signals and the potential for exceptions that might still allow certain types of processing.
6. The Importance of Clear Definitions and Terminology:
- 37:28 – 37:52: The call for “crisp definitions outside of where they get used” is a direct plea for clarity. For SEOs, this means that the underlying vocabulary and definitions will be crucial for advising clients on how to correctly implement these signals. Ambiguous definitions lead to incorrect implementation.
7. The “Mapping to Preferences” and Syntax:
- 41:03 – 01:06:29: The discussion on how preferences are mapped and the use of an “exemplary syntax” is key.
- Future of website signals: SEOs will need to understand and implement these new syntaxes or signals. The ability to map existing mechanisms (like robots.txt) to this new vocabulary is a practical concern.
- Extensibility: The mention of extensibility and the need for RFCs to add new terms (00:17:02.800 – 00:17:38.480) suggests that this is a living standard, and SEOs will need to stay updated on new developments.
In summary, for an SEO consultant, this transcript highlights:
- New tools for content control: Websites will have more granular ways to signal their wishes regarding AI processing.
- The evolution of robots.txt: Its role is expanding beyond just crawl directives to include AI usage preferences.
- The critical “search” carve-out: This is essential for ensuring AI preference signals don’t accidentally block traditional search engine access.
- The need for clear definitions: Ambiguity in terms like “generative” or “inference” will require careful interpretation and implementation guidance.
- The interplay of technical signals and broader legal/contractual contexts.
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