As Predicted, Judge Dismisses Nearly All Of Sarah Silverman, Michael Chabon, And Other Authors’ Lawsuits Against OpenAI

Copyright

from the copyright-law-has-rules dept

Can’t say we didn’t warn everyone. Last summer we pointed out that Sarah Silverman and a bunch of other authors suing AI companies for copyright infringement seemed to only demonstrate that they didn’t understand how copyright works.

And, now Judge Araceli Martinez-Olguin, has dismissed most of the claims in three related cases from authors against OpenAI, noting that their theories are just not how copyright law works. The judge does leave them open to amend the claims, but it’s difficult to see how any of the cases will survive. Open AI sought to dismiss all claims except for the direct infringement claim. In its motion to dismiss, OpenAI notes that they will seek to resolve the direct infringement question as a matter of law later in the case (i.e., they will seek summary judgment on it, likely arguing fair use).

For the rest, though, they seek to dismiss the claims outright, and mostly got exactly what they wanted. First up, there’s the pernicious “vicarious copyright infringement” claims that are frequently brought in cases, but rarely hold up. They certainly don’t hold up here:

Plaintiffs suggest that they do not need to allege a “substantial similarity” because they have evidence of “direct copying.” ECF 48 (“Response”) at 15. They argue that because Defendants directly copied the copyrighted books to train the language models, Plaintiffs need not show substantial similarity. Id. at 15 (citing Range Rd. Music, Inc. v. E. Coast Foods, Inc., 668 F.3d 1148, 1154 (9th Cir. 2012) (explaining that “substantial similarity” helps determine whether copying occurred “when an allegedly infringing work appropriates elements of an original without reproducing it in toto.”). Plaintiffs misunderstand Range Rd. There, the court did not need to find substantial similarity because the infringement was the public performance of copyrighted songs at a bar. Range Rd., 668 F.3d at 1151-52, 1154. Since the plaintiffs provided unrebutted evidence that the performed songs were the protected songs, they did not need to show that they were substantially similar. Id. at 1154. Distinctly, Plaintiffs here have not alleged that the ChatGPT outputs contain direct copies of the copyrighted books. Because they fail to allege direct copying, they must show a substantial similarity between the outputs and the copyrighted materials. See Skidmore, 952 F.3d at 1064; Corbello, 974 F.3d at 973-74.

Plaintiffs’ allegation that “every output of the OpenAI Language Models is an infringing derivative work” is insufficient. Tremblay Compl. ¶ 59; Silverman Compl. ¶ 60. Plaintiffs fail to explain what the outputs entail or allege that any particular output is substantially similar – or similar at all – to their books. Accordingly, the Court dismisses the vicarious copyright infringement claim with leave to amend.

Next up were the always weak DMCA 1202 claims about the “removal or alteration of copyright management information.” That also does not fly:

Even if Plaintiffs provided facts showing Defendants’ knowing removal of CMI from the books during the training process, Plaintiffs have not shown how omitting CMI in the copies used in the training set gave Defendants reasonable grounds to know that ChatGPT’s output would induce, enable, facilitate, or conceal infringement. See Stevens, 899 F.3d at 673 (finding that allegations that “someone might be able to use [the copyrighted work] undetected . . . simply identifies a general possibility that exists whenever CMI is removed,” and fails to show the necessary mental state). Plaintiffs argue that OpenAI’s failure to state which internet books it uses to train ChatGPT shows that it knowingly enabled infringement, because ChatGPT users will not know if any output is infringing. Response at 21-22. However, Plaintiffs do not point to any caselaw to suggest that failure to reveal such information has any bearing on whether the alleged removal of CMI in an internal database will knowingly enable infringement. Plaintiffs have failed to state a claim under Section 12(b)(1)

Same thing with 1202(b)(3) regarding the alleged distribution of copies. That’s a problem since they don’t show any distribution of copies:

Under the plain language of the statute, liability requires distributing the original “works” or “copies of [the] works.” 17 U.S.C. § 1202(b)(3). Plaintiffs have not alleged that Defendants distributed their books or copies of their books. Instead, they have alleged that “every output from the OpenAI Language Models is an infringing derivative work” without providing any indication as to what such outputs entail – i.e., whether they are the copyrighted books or copies of the books. That is insufficient to support this cause of action under the DMCA.

Plaintiffs compare their claim to that in Doe 1, however, the plaintiffs in Doe 1 alleged that the defendants “distributed copies of [plaintiff’s licensed] code knowing that CMI had been removed or altered.” Doe 1, 2023 WL 3449131, at *11. The Doe 1 plaintiffs alleged that defendants knew that the programs “reproduced training data,” such as the licensed code, as output. Id. Plaintiffs here have not alleged that ChatGPT reproduces Plaintiffs copyrighted works without CMI.

Then there are the unfair competition claims. Here, one part of the claim remains standing, but the rest are dismissed. As the court notes, for there to be unlawful competition, they need to show an act is “unlawful, unfair, or fraudulent.” Here two of the three prongs fail. First up “unlawful.”

Even if Plaintiffs can bring claims under the DMCA, they must show economic injury caused by the unfair business practice. See Davis v. RiverSource Life Ins. Co., 240 F. Supp. 3d 1011, 1017 (N.D. Cal. 2017) (quoting Kwikset Corp. v. Superior Ct., 51 Cal. 4th 310, 322 (2011)). Defendants argue that Plaintiffs have not alleged that they have “lost money or property.” Motion at 29-30; see Kwikset Corp., 51 Cal. 4th at 322-23. Plaintiffs counter that they have lost intellectual property in connection with the DMCA claims because of the “risk of future damage to intellectual property that results the moment a defendant removes CMI from digital copies of Plaintiffs’ work – copies that can be reproduced and distributed online at near zero marginal cost.” Response at 28. However, nowhere in Plaintiffs’ complaint do they allege that Defendants reproduced and distributed copies of their books. Accordingly, any injury is speculative, and the unlawful prong of the UCL claim fails for this additional reason.

What about fraudulent? Nope. No good.

Plaintiffs also argue that they pleaded UCL violations based on “fraudulent” conduct. Response at 26-27. They point to a paragraph in the complaint that states that “consumers are likely to be deceived” by Defendants’ unlawful practices and that Defendants “deceptively designed ChatGPT to output without any CMI.” Tremblay Compl. ¶ 72. The allegation’s references to CMI demonstrates that Plaintiffs’ claims rest on a violation of the DMCA, and thus fail as the Court has dismissed the underlying DMCA claim. Supra Sections B, C(1). To the extent that Plaintiffs ground their claim in fraudulent business practices, Plaintiffs fail to indicate where they have pleaded allegations of fraud. Thus, they fail to satisfy the heightened pleading requirements of Rule 9(b) which apply to UCL fraud claims. See Armstrong-Harris, 2022 WL 3348246, at *2. Therefore, the UCL claim based on fraudulent conduct also fails.

The only prong that remains is “unfair,” which the court notes, California defines broadly, and thus it survives, for now. Given everything else in the opinion, though, it feels like this one prong is also ripe for dismissal at the summary judgment stage.

Then there’s “negligence.” Plaintiffs’ lawyers love to claim negligence, but it rarely stands up. You can’t just take “this thing is bad” and claim negligence. Here, the plaintiffs went to even more ridiculous levels, arguing that OpenAI had a made up “duty of care” to protect the copyrights of the authors, and the failure to do that was negligent. As the court notes, that’s not how this works:

The Complaints allege that Defendants negligently maintained and controlled information in their possession. Tremblay Compl. ¶¶ 74-75; Silverman Compl. ¶¶ 75-76. Plaintiffs argue without legal support that Defendants owed a duty to safeguard Plaintiffs’ works. Response at 30. Plaintiffs do not identify what duty exists to “maintain[] and control[]” the public information contained in Plaintiffs’ copyrighted books. The negligence claim fails on this basis.

Plaintiffs’ argument that there is a “special relationship” between the parties also fails. See Response at 30. Nowhere in the Complaints do Plaintiffs allege that there is any fiduciary or custodial relationship between the parties. Plaintiffs do not explain how merely possessing their books creates a special relationship, citing only to an inapposite case where defendants were custodians of plaintiffs’ “personal and confidential information.” Witriol v. LexisNexis Grp., No. C05-02392 MJJ, 2006 WL 4725713, at *8 (N.D. Cal. Feb. 10, 2006).

As Plaintiffs have not alleged that Defendants owed them a legal duty, the Court dismisses this claim with leave to amend.

Finally, there’s the “unjust enrichment” claim which also fails, because there’s no evidence that any benefit to OpenAI came from “mistake, fraud, coercion or request.”

Defendants argue that this claim must be dismissed because Plaintiffs fail to allege what “benefit” they quasi-contractually “conferred” on OpenAI or that Plaintiffs conferred this benefit through “mistake, fraud, or coercion.” Motion at 32 (citing Bittel Tech., Inc. v. Bittel USA, Inc., No. C10-00719 HRL, 2010 WL 3221864, at 5 (N.D. Cal. Aug. 13, 2010) (“Ordinarily, a plaintiff must show that the benefit was conferred on the defendant through mistake, fraud or coercion.”) (citation omitted). Plaintiffs fail to allege that OpenAI “has been unjustly conferred a benefit ‘through mistake, fraud, coercion, or request.’” See Astiana, 783 F.3d at 762 (citation omitted); LeGrand v. Abbott Lab’ys, 655 F. Supp. 3d 871, 898 (N.D. Cal. 2023) (same); see, e.g., Russell v. Walmart, Inc., No. 22-CV-02813-JST, 2023 WL 4341460, at 2 (N.D. Cal. July 5, 2023) (“it is not enough that Russell have provided Walmart with a beneficial service; Russell must also allege that Walmart unjustly secured that benefit through qualifying conduct. Absent qualifying mistake, fraud, coercion, or request by Walmart, there is no injustice.”). As Plaintiffs have not alleged that OpenAI unjustly obtained benefits from Plaintiffs’ copyrighted works through fraud, mistake, coercion, or request, this claim fails

The court does allow the plaintiffs to amend, and it is almost guaranteed that an amended complaint will be forthcoming. But given the underlying reasons for dismissing all of those claims, I find it hard to believe that they’ll amend it in a way that will succeed.

Of course, there are still the two other claims that survive, but both seem likely to be in trouble by the time this case gets to summary judgment.

I know that many people wanted this case to be a winner, in part because they dislike generative AI in general, or OpenAI specifically. Or, in some cases, because they’re fans of the authors involved. But this case is about the specifics of copyright, and you have to allege specific facts to make it a copyright case, and (as we noted) these cases were ridiculously weak from the jump.

And the judge saw that.

Filed Under: ai, copyright management information, direct infringement, dmca, fair use, generative ai, michael chabon, negligence, paul tremblay, sarah silverman, unfair competition, vicarious infringement
Companies: openai