Elsevier

Anthropic's $1.5B Copyright Settlement Approved

Anthropic reached a court-approved $1.5 billion class-action settlement resolving authors’ claims that its Claude models were trained using pirated books. The fund will compensate affected authors and publishers — roughly 500,000 works are estimated eligible, with proposed payments of about $3,000 per eligible work — and cancels a planned jury trial. Judge Araceli Martinez-Olguin gave final approval after earlier proceedings in which Judge William Alsup found Anthropic had used pirated sources (including piracy sites) but also held that training on copyrighted books can, in some circumstances, be fair use. Because Anthropic settled rather than appeal, the case will not create binding nationwide precedent; related lawsuits against Google, Meta, Midjourney and OpenAI remain active. Participating plaintiff firms are slated to receive over $100 million in fees.

How NHS 24 and Elsevier are turning uncertainty into confident, clinically safe decisions

The featured story on the Elsevier About page has been updated from 'The future we build could depend on research we don’t read' to a new case study about NHS 24, highlighting a partnership to improve clinical decision-making.

Book Publishers Sue Google Over AI Training

A coalition of major publishers and authors — including Hachette Book Group, Cengage, Elsevier, novelist Scott Turow and S.C.R.I.B.E. — filed a class-action lawsuit against Google on July 14, 2026 in the U.S. District Court for the Southern District of New York. The complaint alleges Google trained its Gemini models on copyrighted books sourced from Google Books and titles uploaded to Google Play without permission, and removed or altered copyright information to conceal that use. Plaintiffs cite internal Google estimates of potential liabilities in the tens to hundreds of billions and say the practice displaces sales and undermines licensing markets. The filing is part of a broader wave of litigation over AI training data and follows publisher tactics such as crawler blocks and threats to delist from search.