OpenAI’s bid to centralize IP combinations follows discovery setbacks

OpenAI Inc. Efforts to centralize eight copyright suits into multidistrict litigation could be a tactic to soften a recent ruling that the company faces a key claim brought by Intercept Media Inc. and slow down some of the proceedings the most advanced, lawyers say.

Judge Jed S. Rakoff on November 21 refused to dismiss Intercept Media’s claim that OpenAI intentionally removed copyright management information from the media outlet’s work in violation of the Digital Millennium Copyright Act in order to use it to form ChatGPT. Her order of the United States District Court for the Southern District of New York departs from other decisions issued by judges of the the same neighborhood And California who dismissed similar complaints against the artificial intelligence company.

The company is involved in discovery battles over its messages from leaders on social networksand we seek, without success, to obtain income dataAnd journalists’ notes of certain plaintiffs in these cases.

OpenAI informed SDNY Magistrate Judge Ona T. Wang of its decision to petition the Judicial Committee on Multidistrict Litigation at a status conference on December 3 and two days later filed a complaint. letter in the United States District Court for the Northern District of California for inform him of his decision.

MDL centralizes pretrial activities such as discovery in cases involving common factual issues. Although it might be more procedurally efficient for an MDL court to handle all pretrial proceedings for all eight lawsuits, including those brought by New York Times Co. and authors like comedian Sarah Silverman — the MDL court could also potentially rule on dispositive motions like summary judgment, Santa Clara University School of Law professor Edward Lee said. That “would be quite different from multiple judges” in New York and California to a single judge before trial, he said.

But consolidating findings in all cases “would ultimately slow down litigation since the cases are at different points and some would have to catch up,” said Marc Lemleyprofessor of intellectual property at Stanford Law School who also represents Meta Platforms Inc. and Stability AI in copyright suits over training data. Some plaintiffs objected Previous OpenAI merger motions certain lawsuits and would also have the opportunity to litigate against an MDL petition.

OpenAI’s bid for MDL “could be an end to Judge Rakoff’s opinion that is out of step with all of these other decisions,” Lemley said. OpenAI can tell the MDL panel: “We are now facing inconsistencies in decisions and we want them to be consolidated,” he said.

The New York Times declined to comment, emphasizing that OpenAI’s petition had not been filed.

“We have no comment to make on this matter beyond what is contained in the letter itself,” OpenAI said in an emailed statement.

Over time, judges who receive MDL jurisdiction have gained more power to resolve motions to dismiss and motions for summary judgment, said Michael Kaufmanndean and professor at Santa Clara Law. The judge could go so far as to hold a benchmark trial, he added, as a test case for the most controversial issues.

Leaving power in the hands of a judge could potentially disadvantage plaintiffs in other ways as well, James Gatto by Sheppard Mullin said. For example, it could limit the number of “bites at the apple” they receive in testing different theories in different courts.

“Often when you’re trying to resolve new legal issues like this, you often see plaintiffs take various tactics, raise different issues in different cases, to see what sticks,” he said.

MDL Assignment

Because case assignment is up to the MDL panel — not the litigants — parties may be uncertain about which judge or judges will conduct those proceedings, Kaufman said. There is no guarantee that OpenAI will find a favorable judge in MDL.

The judicial panel could even nominate Rakoff, Lemley added.

OpenAI could also seek an MDL to limit each of its witnesses to a single deposition instead of requiring them to face separate depositions for each trial, Santa Clara’s Lee said.

To successfully centralize all cases in a single court, OpenAI will need to show that there are common questions of fact in all cases and that the transfer would be practical and cost-effective. Although each of the cases focuses on different types of content (news, books, images), it could be argued that they all involve copyrighted material that OpenAI allegedly copied to train AI systems, Gatto said.

“The facts don’t have to be the same for an MDL,” he said, “but they do have to be similar. »

The centralization of files could, however, create complications, particularly with regard to the new issues involved. If the cases returned to their original courts for trial, it would open up the possibility of setting an adversarial precedent. In the absence of an interlocutory appeal while the case was still consolidated, the parties would raise their objections in a post-trial motion in the separate courts, Fabio Marin by Womble Dickinson Bond said. Appeals of any decision made after trial could lead to an appeal of the same issue in different circuit courts.

“In theory, there could be different decisions from different appeals courts on essentially the same issue,” Marino said.