Tennessee has joined the ranks of states regulating, in various ways, the use of artificial intelligence to manipulate an individual’s likeness.  On March 21, 2024, Gov. Bill Lee said “thank you very much” to the Tennessee legislature and signed into law the Ensuring Likeness, Voice, and Image Security (“ELVIS”) Act of 2024, HB 2091/SB 2096

Last week, we asked for your input on whether certain images generated by AI programs were substantially similar to the Plaintiffs’ original artworks, as alleged in Andersen v. Stability AI

Orders issued in the Andersen case (and other, similar cases) to date suggest that the success of the plaintiffs’ claims hinges on being able

On Wednesday, the Supreme Court heard oral argument in Warner Chappell Music, Inc. v. Nealy, an appeal of the Eleventh Circuit’s determination that a copyright plaintiff can recover damages for infringement occurring more than three years prior to filing suit. The Eleventh Circuit’s decision was based on the discovery accrual rule, which begins the limitations period at the moment a plaintiff becomes aware of or should reasonably learn of the infringement upon which a claim is based.

Sherman Nealy and Music Specialist, Inc. brought the underlying lawsuit against Warner and others based upon the alleged unauthorized licensing and use of songs owned by the plaintiffs. Much of alleged infringement occurred while Nealy was incarcerated, and he alleged that he did not become aware of the infringement until 2016. Nealy filed suit in 2018, within three years of the date he allegedly discovered the infringement.  The district court held that Nealy’s claims were timely, but that he could only obtain damages for the three years prior to the filing of his lawsuit. The Eleventh Circuit overturned the finding that such a limit on damages existed, holding that Nealy could potentially recover damages outside the three-year period.Continue Reading Skeptical of the Second Circuit: U.S. Supreme Court Hears Arguments on Copyright Damages

You might recall that the judge in  Andersen v. Stability AI —the case in which a group of visual artists sued the makers of several different generative AI platforms for copyright infringement—tossed most of the plaintiffs’ claims last year. However, the court allowed the plaintiffs an opportunity to replead. Specifically, the judge said that for their vicarious copyright infringement claims to remain viable, the plaintiffs would have to at least allege that derivative works created using AI programs that generate images in response to user prompts are “substantially similar” to their original copyright-protected works.

The plaintiffs took the judge’s ruling to heart. They filed an amended complaint, adding new plaintiffs and using statements by the AI companies’ employees on social media to bolster their claims that the AI programs are copying their art. Most interesting to us, however, was the images the plaintiff artists inserted into their amended pleading providing a side-by-side comparison of their original visual works and what they allege is substantially similar AI-generated output. (Plaintiffs in other cases involving written works have been taking notes on the Stability AI decision and similar decisions too, which we’ll be writing about in the coming weeks).Continue Reading Reader Survey: Tell Us Whether You Think Stability AI Outputs are Substantially Similar to Andersen Plaintiffs’ Original Works

The class of plaintiff authors seeking to hold OpenAI liable for copyright infringement has faced yet another setback. The U.S. District Court for the Northern District of California has knocked out the majority of their claims, refusing to accept the blanket allegation that “every output of the OpenAI Language Model is an infringing derivative work.” However, the court has allowed the plaintiffs another chance to cure many of the deficiencies in their pleadings, so the battle is not yet over.

As we’ve previously reported, named plaintiffs including Paul Tremblay, Sarah Silverman, and Michael Chabon have filed class action lawsuits against several companies associated with popular Large Language Model tools like ChatGPT. The lawsuits claim that because the defendants copied their original works of authorship to use as training material for the LLMs, the AI companies are liable under the federal Copyright Act and various state tort laws. For a quick recap of the theories they are asserting, check out our recent AI Update.Continue Reading The Latest Chapter in Authors’ Copyright Suit Against OpenAI: Original Pleadings Insufficient

Thursday, January 25, 2024
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About the Program

Join Seyfarth partners Ken Wilton and Lauren Leipold for an examination of pivotal 2023 developments in trademark litigation, from U.S. Supreme Court decisions to new guidance from federal appellate courts, district courts, and the USPTO. This webinar will provide actionable takeaways for your legal practice in 2024, from doctrinal shifts in the application of trademark law to technicalities in TTAB procedure. Learn how these developments will impact the ongoing protection, maintenance, and enforcement of trademarks in the United States and beyond.

Speakers

Kenneth Wilton, Partner, Seyfarth Shaw LLP

Lauren Leipold, Partner, Seyfarth Shaw LLPContinue Reading Upcoming Webinar! How to Win Your Next Trademark Battle: Lessons Learned in 2023

In the latest skirmish between Sarah Silverman and other authors against Chat GPT-maker OpenAI, OpenAI submitted a new decision from a California federal court in support of its attempt to dismiss the Silverman plaintiffs’ claims. According to OpenAI, that other court rejected theories and claims that are nearly identical to Silverman’s claims against OpenAI. If the court hearing Silverman’s claims agrees, copyright holders looking to sue AI companies in the future may find themselves facing long odds on certain claims.

The new California decision cited by OpenAI comes in the wake of a similar decision in a case involving an AI image generator. Like the court in that image-generator case, the new decision cited by OpenAI dismissed most of the plaintiffs’ copyright claims and other claims, although it did so with leave to amend all but one state-law negligence claim. The court in this new decision rejected as “nonsensical” the plaintiffs’ argument that large language models (or LLMs) “are themselves infringing derivative works,” holding that “[t]here is no way to understand the [LLMs] themselves as a recasting or adaptation of any of the plaintiffs’ books.” Similarly, the court rejected the notion that “every output of the [LLMs] is an infringing derivative work,” stating that “the complaint offers no allegation of the contents of any output, let alone of one that could be understood as recasting, transforming, or adapting the plaintiffs’ books. Without any plausible allegation of an infringing output, there can be no vicarious infringement.”Continue Reading “The Plaintiffs Are Wrong”: OpenAI Submits New Authority in Attempt to Knock Out Sarah Silverman’s Claims