OpenAI desperate to avoid explaining why it deleted pirated book datasets
Not for OpenAI to reason why?
OpenAI risks increased fines after deleting pirated books datasets.
OpenAI may soon be forced to explain why it deleted a pair of controversial datasets composed of pirated books, and the stakes could not be higher.
At the heart of a class-action lawsuit from authors alleging that ChatGPT was illegally trained on their works, OpenAI’s decision to delete the datasets could end up being a deciding factor that gives the authors the win.
It’s undisputed that OpenAI deleted the datasets, known as “Books 1” and “Books 2,” prior to ChatGPT’s release in 2022. Created by former OpenAI employees in 2021, the datasets were built by scraping the open web and seizing the bulk of its data from a shadow library called Library Genesis (LibGen).
As OpenAI tells it, the datasets fell out of use within that same year, prompting an internal decision to delete them.
But the authors suspect there’s more to the story than that. They noted that OpenAI appeared to flip-flop by retracting its claim that the datasets’ “non-use” was a reason for deletion, then later claiming that all reasons for deletion, including “non-use,” should be shielded under attorney-client privilege.
To the authors, it seemed like OpenAI was quickly backtracking after the court granted the authors’ discovery requests to review OpenAI’s internal messages on the firm’s “non-use.”
In fact, OpenAI’s reversal only made authors more eager to see how OpenAI discussed “non-use,” and now they may get to find out all the reasons why OpenAI deleted the datasets.
Last week, US district judge Ona Wang ordered OpenAI to share all communications with in-house lawyers about deleting the datasets, as well as “all internal references to LibGen that OpenAI has redacted or withheld on the basis of attorney-client privilege.”
According to Wang, OpenAI slipped up by arguing that “non-use” was not a “reason” for deleting the datasets, while simultaneously claiming that it should also be deemed a “reason” considered privileged.
Either way, the judge ruled that OpenAI couldn’t block discovery on “non-use” just by deleting a few words from prior filings that had been on the docket for more than a year.
“OpenAI has gone back-and-forth on whether ‘non-use’ as a ‘reason’ for the deletion of Books1 and Books2 is privileged at all,” Wang wrote. “OpenAI cannot state a ‘reason’ (which implies it is not privileged) and then later assert that the ‘reason’ is privileged to avoid discovery.”
Additionally, OpenAI’s claim that all reasons for deleting the datasets are privileged “strains credulity,” she concluded, ordering OpenAI to produce a wide range of potentially revealing internal messages by December 8. OpenAI must also make its in-house lawyers available for deposition by December 19.
OpenAI has argued that it never flip-flopped or retracted anything. It simply used vague phrasing that led to confusion over whether any of the reasons for deleting the datasets were considered non-privileged. But Wang didn’t buy into that, concluding that “even if a ‘reason’ like ‘non-use’ could be privileged, OpenAI has waived privilege by making a moving target of its privilege assertions.”
Asked for comment, OpenAI told Ars that “we disagree with the ruling and intend to appeal.”
OpenAI’s “flip-flop” may cost it the win
So far, OpenAI has avoided disclosing its rationale, claiming that all the reasons it had for deleting the datasets are privileged. In-house lawyers weighed in on the decision to delete and were even copied on a Slack channel initially called “excise-libgen.”
But Wang reviewed those Slack messages and found that “the vast majority of these communications were not privileged because they were ‘plainly devoid of any request for legal advice and counsel [did] not once weigh in.’”
In a particularly non-privileged batch of messages, one OpenAI lawyer, Jason Kwon, only weighed in once, the judge noted, to recommend the channel name be changed to “project-clear.” Wang reminded OpenAI that “the entirety of the Slack channel and all messages contained therein is not privileged simply because it was created at the direction of an attorney and/or the fact that a lawyer was copied on the communications.”
The authors believe that exposing OpenAI’s rationale may help prove that the ChatGPT maker willfully infringed on copyrights when pirating the book data. As Wang explained, OpenAI’s retraction risked putting the AI firm’s “good faith and state of mind at issue,” which could increase fines in a loss.
“In a copyright case, a court can increase the award of statutory damages up to $150,000 per infringed work if the infringement was willful, meaning the defendant ‘was actually aware of the infringing activity’ or the ‘defendant’s actions were the result of reckless disregard for, or willful blindness to, the copyright holder’s rights,’” Wang wrote.
In a court transcript, a lawyer representing some of the authors suing OpenAI, Christopher Young, noted that OpenAI could be in trouble if evidence showed that it decided against using the datasets for later models due to legal risks. He also suggested that OpenAI could be using the datasets under different names to mask further infringement.
Judge calls out OpenAI for twisting fair use ruling
Wang also found it contradictory that OpenAI continued to argue in a recent filing that it acted in good faith, while “artfully” removing “its good faith affirmative defense and key words such as ‘innocent,’ ‘reasonably believed,’ and ‘good faith.’” These changes only strengthened discovery requests to explore authors’ willfulness theory, Wang wrote, noting the sought-after internal messages would now be critical for the court’s review.
“A jury is entitled to know the basis for OpenAI’s purported good faith,” Wang wrote.
The judge appeared particularly frustrated by OpenAI seemingly twisting the Anthropic ruling to defend against the authors’ request to learn more about the deletion of the datasets.
In a footnote, Wang called out OpenAI for “bizarrely” citing an Anthropic ruling that “grossly” misrepresented Judge William Alsup’s decision by claiming that he found that “downloading pirated copies of books is lawful as long as they are subsequently used for training an LLM.”
Instead, Alsup wrote that he doubted that “any accused infringer could ever meet its burden of explaining why downloading source copies from pirate sites that it could have purchased or otherwise accessed lawfully was itself reasonably necessary to any subsequent fair use.”
If anything, Wang wrote, OpenAI’s decision to pirate book data—then delete it—seemed “to fall squarely into the category of activities proscribed by” Alsup. For emphasis, she quoted Alsup’s order, which said, “such piracy of otherwise available copies is inherently, irredeemably infringing even if the pirated copies are immediately used for the transformative use and immediately discarded.”
For the authors, getting hold of OpenAI’s privileged communications could tip the scales in their favor, the Hollywood Reporter suggested. Some authors believe the key to winning could be testimony from Anthropic CEO Dario Amodei, who is accused of creating the controversial datasets while he was still at OpenAI. The authors think Amodei also possesses information on the destruction of the datasets, court filings show.
OpenAI tried to fight the authors’ motion to depose Amodei, but a judge sided with the authors in March, compelling Amodei to answer their biggest questions on his involvement.
Whether Amodei’s testimony is a bombshell remains to be seen, but it’s clear that OpenAI may struggle to overcome claims of willful infringement. Wang noted there is a “fundamental conflict” in circumstances “where a party asserts a good faith defense based on advice of counsel but then blocks inquiry into their state of mind by asserting attorney-client privilege,” suggesting that OpenAI may have substantially weakened its defense.
The outcome of the dispute over the deletions could influence OpenAI’s calculus on whether it should ultimately settle the lawsuit. Ahead of the Anthropic settlement—the largest publicly reported copyright class action settlement in history—authors suing pointed to evidence that Anthropic became “not so gung ho about” training on pirated books “for legal reasons.” That seems to be the type of smoking-gun evidence that authors hope will emerge from OpenAI’s withheld Slack messages.
Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.
