Hi Norm, Christian and all other responders,

I really appreciate the initiative and believe that the driving force behind it is the wish to ensure high quality and credibility of QT4. And I absolutely share Christian's thoughts on  pushing the limits of what is possible and what has always been driven by science and technology.

The first question that naturally arises is how to implement such a policy in practice. Who, and using what mechanism, will judge the originality of the work?

Will this not be rather subjective, biased and sometimes even bordering on censorship and witch hunting?

This is a large and very important problem and at present entire organizations and specialized events are focusing on it.

For example the World Conference on Work Integrity (WCRI) that was held this month in Vancouver:

https://www.science.org/content/article/researchers-aim-universal-ai-disclosure-guidelines-devil-details?utm_source=Live+Audience&utm_campaign=26612afd6a-nature-briefing-ai-robotics-20260519&utm_medium=email&utm_term=0_-b08e196e33-49392792

A quote from this:

" “Researchers should disclose AI idea generation, even when none of those ideas are ultimately included in the final manuscript.” Dozens of attendees walk over to a sign marked “strongly disagree”; a few stand firm under the sign for “strongly agree.” The room erupts in uncomfortable laughter. "

In my personal opinion, we should fight plagiarism and lack of originality in any form - not only AI-generated, but any form, even it being human-only plagiarism and mediocrity. 

As a base for objectivity, let us use the below Human Originality Index (HOI) - a scale from 0 to 10 for evaluating content, where 0 corresponds to entirely derivative, automated and lacking novelty content, and 10 corresponds to historically transformative and deeply human insight. We then may agree that only content at or above a certain level (say, 5) of the HOI scale may be allowed.

Here is a first attempt at defining such a HOI index:
0 - Pure Reproduction
1 - Mechanical Compilation
2 - Surface Variation

3 - Directed Assembly
4 - Skilled Adaptation

5 - Meaningful Synthesis

6 - Distinctive Personal Contribution

7 - Significant Innovation

8 - Field-Changing Originality

9 - Civilization-Level Breakthrough

10 -Foundational Transformation

Or, more simplified groupings:

0–2 Reproduction and mimicry
3–4 Adaptation and assembly
5–6 Authentic human synthesis
7–8 Major innovation
9–10 Transformative breakthroughs

Or a 2-dimensional alternative:

Human Authorship (0–10)
Originality (0–10)

For example:

Fully AI-generated summary: Authorship 1, Originality 1
Human essay with AI editing: Authorship 8, Originality 6
Groundbreaking theory developed with AI assistance: Authorship 9, Originality 10

And finally, I asked ChatGPT, whether or not he thinks my email (this message) was "AI-generated".

Here is his response, with no further comment:

https://chatgpt.com/s/t_6a175acb41508191b0e4658f871ac636

Hope that this helps,
Dimitre.

On Wed, May 27, 2026 at 12:43 PM Christian Grün <cg@basex.org> wrote:

Norm,

Thank you for drafting the proposal. I fully appreciate your initiative and the effort to define rules on how to deal with AI in our group.

We are all flooded with non-human content today. At the same time, it becomes increasingly difficult to tell whether AI was used to refine, revise or create an existing text (ironically, the most reliable way to detect it is often the same technology). The more flawless a text seems, the higher the chances are that AI was used to generate it. Which is a curse, since professionalism is the very essence of what we strive for. Next, content creators themselves often cannot tell anymore how much AI is involved when translators, spell/content checkers, or web search are used. Finally, if we access existing sources, including scientific papers, we cannot tell how they came into existence either.

In short, AI is here to stay, its quality is improving rapidly, and it will become impossible to assess whether it was part of a creative process. The interesting practical questions for me would be whether and how its influence harms our daily work. I can only think of very basic guidelines, as follows:

• With regard to contributions, as the origin becomes fuzzier, we should continue to expect each contributor to be able to explain every single bit of their work.
• With regard to reviews and testing, new technologies should in no way cause extra effort.

Incidentally, both questions do not really revolve around AI. Thus, my (very personal) conclusion tends to be that the growing predominance of AI should in no way push us to become more permissive regarding contributions. A work shouldn’t expect to be consumed, let alone taken seriously, simply because it exists. We should continue to reject everything we are not fully convinced is an improvement over the status quo.

Having said this, I share your general concern that AI will have a vast effect on all of us. Pushing the limits of what is possible has always driven science and technology – for better (we might otherwise never have met electronically) and for worse. The open and important question is how much we want to be part of an ongoing and potentially destructive process. I think that a policy on AI is definitely something from which we will benefit, even if it does not establish fixed rules.

However we decide, I am sure it will be an improvement. Even if we decide to be as strict as possible, it will still help us to rethink our position later, once AI has evolved further.

Thanks,
Christian
________________________________________

Von: Norm Tovey-Walsh <norm@saxonica.com>
Gesendet: Montag, 25. Mai 2026 13:51
An: public-xslt-40@w3.org
Betreff: Proposed draft of an AI policy

Per my action, QT4CG-0165-01, here’s an attempt at an AI policy:

Contributions must not include content generated by large language models (LLMs) or other probabilistic tools (including tools which are often colloquially categorized as "AI").

This policy applies to the specifications, tests, issues, comments, pull requests, and any other contributions to QT4CG.

Although we acknowledge the many widely discussed ethical issues with LLMs, we will not refer to those issues as a primary justification for this policy. Instead, the specific justifications for the policy are practical.

For most members of the community group, our efforts are focused on document review. Reviewing technical specifications requires comparing what the specification says with an understanding of what was proposed by the group and determining if they are aligned. This is a time-consuming process.

LLMs are exceptionally good at producing large volumes of very /plausible/ text, but that plausibility is a statistical parlour trick: the LLM does not understand and cannot evaluate the output against any objective criteria.

Any process that increases the volume of material that has to be reviewed must be held to the highest standard of intellectual contribution.

A secondary practical concern is that LLMs have been trained on an enormous corpus of material, sometimes obtained in violation of copyright and other laws. Their output often includes verbatim samples of the training data. Incorporating such prose into the specifications may unknowingly violate licenses of copyrighted works.

For these practical reasons, QT4CG does not accept content that has been generated or substantially constructed using LLMs, "AI", or any similar probabilistic tools.

If you are uncertain whether the tool you wish to use, or the way in which you wish to use it, is covered by this policy, you are very welcome to discuss it with the CG's Chair.

                                        Be seeing you,
                                          norm

--
Norm Tovey-Walsh
CEO, Saxonica