A new report by digital rights nonprofit Electronic Privacy Information Center has raised concerns over how leading artificial intelligence companies manage user privacy controls and data-sharing opt-out systems.
According to the study, major AI firms including OpenAI, Meta, and Google are allegedly using design practices that make it difficult for users to stop the sharing or sale of their personal data. Researchers claim these methods resemble tactics historically associated with data brokers and other large technology platforms.
The report states that several large language model providers do not clearly display links to opt-out forms through their homepages or privacy policy sections, creating additional barriers for users attempting to control how their information is used.
Based on an audit involving platforms including Meta, X, OpenAI, and Tinder, researchers found that users were often required to log into accounts before being allowed to submit requests to opt out of data-sharing processes. The study argues that such systems can discourage users from exercising privacy rights due to added complexity and lack of transparency.
The findings come amid growing global scrutiny around how AI companies collect, process, and use personal data to train large language models and recommendation systems. As AI adoption accelerates, regulators and digital rights groups have increasingly questioned whether existing privacy protections are sufficient to safeguard user information.
Researchers behind the report suggest that the opt-out mechanisms used by several companies rely on what are often referred to as “dark patterns” — interface designs intended to influence user behavior or make privacy-related decisions harder to navigate. These practices have become a broader concern within the technology industry as governments push for stronger consumer data protections.
The study also highlights concerns around accessibility and transparency, particularly for users who may not fully understand how their information is being used within AI systems. Privacy advocates argue that companies should provide simpler and more visible tools allowing individuals to manage data preferences without unnecessary obstacles.
The issue is gaining significance as generative AI platforms continue expanding rapidly across consumer and enterprise markets. With increasing dependence on large-scale datasets for AI model training, questions surrounding consent, transparency, and user control are becoming central to discussions around responsible AI development.
The report adds to the growing debate over balancing technological innovation with stronger privacy standards and clearer digital rights protections for users worldwide.
