Linkedin sued for sharing users’ private data with third parties to train AI models, accused of using private messages to train AI
LinkedIn is currently facing a class-action lawsuit filed by its Premium customers, who allege that the platform improperly shared their private messages with third parties for the purpose of training AI models. This legal action was initiated in San Jose, California, and represents millions of users who are concerned about the unauthorized use of their private data, particularly InMail messages.
Allegations and Legal Basis
The lawsuit claims that LinkedIn introduced a new privacy setting in August 2024, which automatically opted users into a data-sharing program without their explicit consent. Following this, a privacy policy update on September 18, 2024, stated that user information could be utilized for AI training. The plaintiffs argue that this change was made discreetly to avoid backlash and that opting out of data sharing would not prevent previously shared data from being used for AI training.
The plaintiffs are seeking damages for:
Breaches of contract
Violations of California’s unfair competition laws
$1,000 per affected user under the federal Stored Communications Act.
LinkedIn’s Response
LinkedIn has denied the allegations, asserting that the claims are without merit. A spokesperson for the company emphasized that these accusations are false and highlighted that the changes to privacy policies were not applicable to users in regions such as the UK and the European Economic Area. The company has previously faced similar scrutiny over its data practices, including a settlement in 2024 regarding inflated advertising metrics.
This lawsuit raises significant concerns about user privacy in the context of rapidly evolving AI technologies. It underscores the tension between leveraging user data for technological advancement and maintaining trust with users regarding how their personal information is handled. As privacy issues gain more attention, the outcome of this case could have broader implications for data practices across the tech industry.