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A federal judge dismissed the antitrust case brought by ROSS Intelligence against Thomson Reuters, citing insufficient evidence.
ROSS had accused Thomson Reuters of monopolizing legal research by unlawfully tying its search tool to its public law database.
A separate AI copyright case Thomson Reuters brought against ROSS is still pending.
A federal judge dismissed antitrust claims filed against Thomson Reuters after finding that the plaintiff, former legal research startup ROSS Intelligence failed to provide sufficient evidence to back its case, according to LawNext.com.
ROSS claimed that Thomson Reuters violated federal antitrust law by unlawfully tying its search tool to its public law database in order to maintain its dominance in the overall market for legal search platforms.
ROSS’s insisted that Westlaw caselaw database is a standalone product that many consumers want to buy, but that Thomson Reuters will sell it only when it is packaged with Westlaw’s search tools, which ROSS alleged was a separate product.
In 2022, Judge Leonard P. Stark, who previously presided over the case, dismissed a portion of ROSS’s antitrust claims, but he allowed the tying claim to move forward.
However, Third U.S. Circuit Court of Appeals Judge Stephanos Bibas, sitting by designation in the U.S. District Court in Delaware, granted Thomson Reuters’s motion for summary judgment on the tying claim, concluding that ROSS had failed to back up its allegations with sufficient evidence.
Judge Bibas’s ruling brings an end to ROSS’s counterclaims against Thomson Reuters in an ongoing litigation between the two parties.
An AI copyright suit filed by Thomson Reuters against ROSS is still pending.
Thomson Reuters alleges that ROSS unlawfully used Westlaw legal texts to train its own AI-powered legal research tool.
The AI copyright case was scheduled to go to trial in August 2024, but Judge Bibas postponed it indefinitely.
Filed back in May 2020, this was the first major trial to determine whether AI companies can use copyrighted materials to train their AI models.