If you use Google, you’re training its AI. Here’s how to opt out.
Google updated its privacy settings to allow AI training on user data by default. Users can now opt out through a simple toggle in their account settings.
- Google now uses default settings to allow AI training on user data unless explicitly opted out.
- Users can disable AI data training via a toggle in their Google Account settings.
- The change highlights Google’s focus on leveraging user data for AI model improvements.
- Privacy advocates criticize the lack of prominent transparency in the update.
Google has quietly updated its privacy policy to allow the company to use data from user interactions, such as searches, images, and voice recordings, to train its AI models by default. This change means that unless users actively opt out, their data may contribute to improving Google’s AI systems, including its large language models and other generative tools.
To opt out, users must navigate to their Google Account settings, where a new toggle labeled 'AI Data Training' can be disabled. The process is straightforward but buried in the account dashboard, which may explain why many users remain unaware of the change. Privacy advocates have raised concerns about transparency, as the default setting prioritizes data collection unless manually adjusted.
The update reflects Google’s broader push to leverage user data for AI development, aligning with its strategy to compete in the generative AI space. However, it also underscores the growing tension between convenience and privacy in the era of data-hungry AI systems.
Source: If you use Google, you’re training its AI. Here’s how to opt out.. Read the full piece at the source.
Developers using Google’s AI APIs or tools should be aware of how user data may influence model training.
Students and general users should understand the implications of default data sharing for AI training.
Users concerned about privacy should review and adjust their Google Account settings.
- AI training
- The process of using data to improve the performance and accuracy of AI models.
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