Anthropic has just announced that Claude will start leaving an invisible mark in the text it generates, in an announcement that may have unintended consequences for expert witnesses.
Supported Claude models will embed machine-readable watermarks into generated text. Anthropic says those marks will travel with the words when copied and pasted into other documents and may survive subsequent editing.
The immediate purpose is provenance. As the volume of AI-generated material increases, watermarking offers a potential means of identifying content that has passed through a particular AI system.
For expert witnesses, however, that raises a rather more difficult question: if an expert report contains an AI watermark, what exactly does that prove?
Perhaps less than might first appear.
Detection is not the same as authorship
One of the most important qualifications comes from Anthropic itself.
Anthropic cautions that detecting its watermark does not establish that Claude wrote or originated the material. Rather, it indicates that the content may have been processed by Claude.
That distinction could be particularly important in expert evidence.
An expert might write an entire report themselves and subsequently ask an AI tool to correct spelling and grammar. Another might use AI to improve the structure of material they have already written. A third might provide their analysis and ask an AI system to turn it into polished prose.
Those activities are quite different from asking an AI system to examine the underlying evidence, perform the analysis and suggest the opinion the expert should express.
Yet all involve AI-generated or AI-processed text.
Consider four possible uses:
- An expert writes their report and uses AI to check spelling and grammar.
- The expert writes the substance but asks AI to improve its structure or expression.
- The expert provides their analysis and asks AI to draft passages expressing it.
- The expert asks AI to analyse the evidence and assist in formulating the opinion.
All involve AI, but they plainly do not raise the same questions about the independence of the expert’s analysis and opinion.
That makes the presence of a watermark potentially useful evidence, but not necessarily evidence of what might initially be assumed.
Provenance of the text is not provenance of the opinion
This is perhaps the central issue for expert witnesses. A watermark may provide evidence about the provenance of the words. It might indicate that Claude, or another AI system using similar technology, has been involved in generating or processing them:
- It cannot, by itself, establish the provenance of the opinion.
- It does not tell us who examined the evidence.
- It does not tell us who identified the relevant issues.
- It does not tell us whether the expert carried out the underlying calculations or analysis.
- And, most importantly, it does not tell us whether the conclusion was independently reached by the expert or suggested by an AI system.
The same paragraph could conceivably carry an AI watermark whether Claude corrected three grammatical errors in it or generated the paragraph from scratch.
For expert evidence, those are very different propositions.
The absence of a watermark proves little too
There is also a problem in the opposite direction.
No watermark does not necessarily mean no AI.
Anthropic acknowledges that detection can become more difficult where generated material has subsequently been heavily edited, paraphrased, translated or combined with other text. A passage may also simply be too short to provide sufficient information for reliable detection.
This creates an important limitation if watermark detection ever begins to be used when examining expert reports.
A positive result may indicate AI involvement without establishing the extent or nature of that involvement whilst a negative result cannot necessarily establish that there was no AI involvement at all.
Watermark detection should therefore not be treated as a binary test of whether an expert “used AI”.
A new question in cross-examination?
The development also raises an interesting practical possibility.
“Your report contains a watermark indicating that it was processed by Claude. How did you use it?”
The answer might be entirely unremarkable.
The expert might explain that they wrote the report themselves and used Claude to check its grammar. They might explain that they used it to condense a lengthy passage they had already written. Alternatively, the answer might reveal that AI played a much greater role in analysing material or formulating the opinions contained in the report.
The takeaway is that whilst the watermark itself cannot distinguish between those situations, it may, however, provide the starting point for questions which can.
That means the increasingly important question may not simply be:
“Did you use AI?”
It may instead be:
“Precisely how did you use it?”
Watermarking is becoming a real technology
Anthropic is not alone in pursuing this approach.
Google has already developed SynthID Text, a watermarking technology for AI-generated text. Rather than inserting a visible label or conventional metadata, SynthID subtly affects the model’s choice of tokens as text is generated. Across a sufficiently long passage, those choices create a statistical signature which can subsequently be detected.
Anthropic has not publicly confirmed that Claude’s watermark uses the same technical method, so the two systems should not be assumed to work identically.
The significance is broader. Text watermarking is moving beyond academic research and into mainstream generative AI products.
If the technology becomes widespread, lawyers, courts and experts may increasingly encounter claims that a document has been identified as having passed through an AI system.
Understanding what such a finding does, and does not, establish will therefore become important.
The expert remains responsible
The Academy’s guidance on the use of Artificial Intelligence by expert witnesses already addresses the more fundamental issue.
AI can be a useful tool, but it cannot substitute for the expert’s own expertise, analysis and opinion. Experts remain responsible for the evidence they give. Where AI has played a significant role, keeping appropriate records of how it was used may also become increasingly important, particularly if the expert is subsequently required to explain that use in court.
Watermarking adds another dimension to that responsibility.
It may make some uses of AI more readily identifiable. But identifying that an AI system touched the words is not the same as establishing who produced the intellectual work behind them.
For expert evidence, that distinction is crucial.
Provenance of the text is not necessarily provenance of the opinion.
As AI provenance technology develops, the ability of an expert to explain what the AI did, what the expert did, and where the opinion actually came from may become increasingly important.