Social media enters the era of user-controlled algorithms

For years, recommendation systems on major social networks largely operated behind the scenes, with platforms deciding which posts, videos, and topics users would see. While people could influence their feeds through likes, follows, and content preferences, the underlying algorithms remained mostly opaque.

That model is now evolving as companies introduce new AI-powered tools that allow users to directly shape their recommendations. Recent updates across several major platforms enable people to indicate the types of content they want to see more or less of, giving them a more active role in training their feeds.

Instead of relying solely on platform-driven recommendations, users can increasingly communicate their interests directly, while algorithms adapt in real time.

Supporters say the approach helps create feeds that better match individual preferences and reduces unwanted content. It may also make recommendation systems easier to understand by providing clearer insight into why certain posts are being shown.

For social media companies, the shift could improve engagement by delivering content that aligns more closely with users' interests and changing preferences.

The trend has accelerated in recent months as platforms roll out new customization features powered by advances in artificial intelligence. These tools allow users to adjust topic preferences, influence recommendations across different sections of an app, and filter content more effectively.

Earlier, Qazinform News Agency reported that the UK plans to ban children under the age of 16 from accessing major social media platforms.