Microsoft’s LinkedIn sued for disclosing customer information to train AI models

By Jonathan Stempel

(Reuters) -Microsoft’s LinkedIn has been sued by Premium customers who said the business-focused social media platform disclosed their private messages to third parties without permission to train generative artificial intelligence models.

According to a proposed class action filed on Tuesday night on behalf of millions of LinkedIn Premium customers, LinkedIn quietly introduced a privacy setting last August that let users enable or disable the sharing of their personal data.

Customers said LinkedIn then discreetly updated its privacy policy on Sept. 18 to say data could be used to train AI models, and in a “frequently asked questions” hyperlink said opting out “does not affect training that has already taken place.”

This attempt to “cover its tracks” suggests LinkedIn was fully aware it violated customers’ privacy and its promise to use personal data only to support and improve its platform, in order to minimize public scrutiny and legal fallout, the complaint said.

The lawsuit was filed in the San Jose, California, federal court on behalf of LinkedIn Premium customers who sent or received InMail messages, and whose private information was disclosed to third parties for AI training before Sept. 18.

It seeks unspecified damages for breach of contract and violations of California’s unfair competition law, and $1,000 per person for violations of the federal Stored Communications Act.

LinkedIn said in a statement: “These are false claims with no merit.”

A lawyer for the plaintiffs had no immediate additional comment.

The lawsuit was filed several hours after U.S. President Donald Trump announced a joint venture among Microsoft-backed OpenAI, Oracle and SoftBank, with a potential $500 billion of investment, to build AI infrastructure in the United States.

The case is De La Torre v. LinkedIn Corp, U.S. District Court, Northern District of California, No. 25-00709.

(Reporting by Jonathan Stempel in New York; Editing by Richard Chang and Rod Nickel)

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