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Lawsuits Against Web Scraping to Train AI
Wednesday, May 29, 2024

Plaintiff’s attorneys have filed a wave of lawsuits against various AI tools under a variety of legal theories. Most have had no success so far. Many of the asserted claims have been dismissed for lack of sufficiently pleaded facts to state a claim or for being legally untenable claims. Some of these dismissals have been without prejudice, meaning the plaintiffs get another chance to properly plead a viable claim. In one of the most recent decisions, claims in a nearly 200 page amended complaint were dismissed without prejudice. In a terse decision, the Court excoriated Plaintiff’s rambling complaint’s unnecessary length and distracting allegations, which according to the Court made “it nearly impossible to determine the adequacy of the plaintiffs’ legal claims.” The Court called out rhetoric and policy grievances that are not suitable for resolution by federal courts, including comparing AI’s risks to humanity to the risks posed by the development of nuclear weapons.

While granting leave to amend, the court admonished that if the amended complaint continues to focus on general policy concerns and irrelevant information in a way that interferes with a clear presentation of the legal claims at issue, it will be dismissed with prejudice. In a final parting shot, the Court stated: “if the plaintiffs manage to state a claim that gets past the pleading stage, they should know that, given the way the current version of the complaint was drafted, it’s unlikely that they or their counsel can be trusted to adequately and responsibly represent the interests of absent class members in a federal lawsuit.” Ouch!

There are legitimate open legal issues with respect to training AI. Various lawsuits are testing different legal theories. But as this decision makes clear, cogent legal claims – and not voluminous ramblings – are necessary to get these claims adjudicated.

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