“As I wrote (and broadcast) recently, LLMs are running out of training data, and the desperation to find more will lead to significant legal consequences when it's revealed exactly how much they stole and from whom they stole it from.”
Our reading, the sentence that was checked:
The hunt for more training data will bring AI companies significant legal consequences once it is revealed how much they stole and from whom.
Assessment: Supported Settled before its deadline on 2026-10-29 Evidence as of
Where and when Ed Zitron wrote it
Where's Your Ed At, They're Looting The Internet, paragraph 52.
- Said
- Source observed
- live page, full text, public
- Evidence as of
- the cutoff for this assessment
- Assessment recorded
- assessment wyea-the-great-looting-of-the-internet-7b3c4b-2-a1
We recorded 21 claims from this post. See every claim from this post.
The wording above is the version this site observed on 2026-10-28. The source may have been edited after 2024-04-15. This page does not claim the wording was captured then.
What the claim commits to
- Kind
- Conditional forecast
- Deadline, as the speaker wrote it
- None stated. This site does not add one.
- Deadline state when assessed
- Settled before its deadline
- Deadline state on 2026-10-29
- Settled before its deadline (the release’s reference date)
Conditions
- when it's revealed how much they stole and from whom (antecedent, stated by the speaker)
From the speaker
- desperation to find more
- will lead to significant legal consequences
- when it's revealed exactly how much they stole and from whom
Our interpretation
- The forecast concerns substantial legal consequences for acquiring training material without authorization. It does not require training itself to be declared unlawful.
- A substantial, court-approved settlement involving an AI developer qualifies. The statement names neither a required number of companies nor a monetary threshold.
- The condition requires public disclosure identifying the scale of acquisition and affected works or rightsholders, not an exhaustive inventory across the entire industry.
- This is a legal-consequences claim, not a forecast of a particular company's financial metric.
Counts as supported if: After the required disclosure, a court judgment, approved settlement, or enforcement action imposes substantial consequences directly connected to acquiring material for AI development.
Counts as contradicted if: A decisive legal resolution forecloses substantial consequences across the conduct covered by the forecast. A victory for one defendant or on one legal theory is insufficient.
Retrospective: these criteria were written after the outcome was public.
Current assessment
Did the forecast come true?
Outcome: Supported
The dated evidence matches what the claim committed to, under the criteria frozen before grading.
Scored on a plain reading. The speaker named no measure for this claim, so it was judged on the reading an informed reader would take, stated below under our interpretation. Both reviews had to find that reading fair.
- Evidence as of
- Deadline state when assessed
- Settled before its deadline
- Assessment recorded
- Policy version
- 2026-10-28.7
Rationale
The court disclosed Anthropic's acquisition of millions of pirated books and subsequently approved a $1.5 billion settlement. That establishes substantial legal consequences connected to obtaining material for AI development. The conclusion concerns acquisition: Anthropic separately won the ruling that the training use was fair use. It also depends on reading the forecast as predicting a substantial industry example, rather than consequences for every company.
Limitations
- One company's settlement does not establish consequences for the entire industry.
- Settlement approval is not a trial verdict finding every allegation proved.
- The records do not prove that data scarcity or desperation caused the acquisitions.
Evidence (4 items)
Supports the claim: U.S. District Court, Northern District of California,
thereby pirated over seven million copies of books
Why it matters here: The order publicly disclosed the scale of acquisition and identified affected authors and works. The event date is the judicial disclosure, rather than the earlier downloads; the order also describes using subsets of the acquired collections to train LLMs.
- Publisher
- U.S. District Court, Northern District of California
- Kind of source
- Regulatory filing
- Describes events of
- Public from
Supports the claim: U.S. District Court, Northern District of California,
the Court hereby GRANTS the motion for final approval
Why it matters here: The court granted final approval of the settlement over the acquired books. This supplies the decisive legal event, rather than merely a proposed agreement.
- Publisher
- U.S. District Court, Northern District of California
- Kind of source
- Regulatory filing
- Describes events of
- Public from
Supports the claim: U.S. District Court, Northern District of California,
The non-reversionary Settlement Fund of $1.5 billion
Why it matters here: The size of the approved settlement establishes a substantial legal consequence. The amount measures the significance of that consequence; it is not being compared with a financial forecast.
- Publisher
- U.S. District Court, Northern District of California
- Kind of source
- Regulatory filing
- Describes events of
- Public from
Context only: U.S. District Court, Northern District of California,
the training use was a fair use.
Why it matters here: Anthropic prevailed on the training-use question. This limits the conclusion: the settlement supports consequences for acquisition, not a finding that training on copyrighted books is generally unlawful.
- Publisher
- U.S. District Court, Northern District of California
- Kind of source
- Regulatory filing
- Describes events of
- Public from
Where it was said (1)
Said once in the sources this register covers.
: Where's Your Ed At, They're Looting The Internet
As I wrote (and broadcast) recently, LLMs are running out of training data, and the desperation to find more will lead to significant legal consequences when it's revealed exactly how much they stole and from whom they stole it from.
- Where
- paragraph 52
- Published
- 2024-04-15
- Source observed
- , live page
- Access
- full text, public
History
Assessment versions
- Assessment wyea-the-great-looting-of-the-internet-7b3c4b-2-a1: Current. Outcome: Supported. Evidence as of 2026-10-28. Public date not recorded.
Recorded events
Assessment publishedBy this site
First assessment published after both reviews and the final-text check passed.
About assessment wyea-the-great-looting-of-the-internet-7b3c4b-2-a1.