Dansday
Instagram is testing new features that give users greater control over the content recommended in their feeds, marking another step in Meta's effort to make its recommendation algorithm more transparent and customizable.
The experimental feature, first reported on 27 June 2026, allows users to influence what types of posts appear in areas such as Explore and recommended content. Instead of relying entirely on Instagram's ranking system, users will be able to adjust their preferences to better match their interests.
For years, social media algorithms have been criticized for surfacing repetitive or unwanted content while giving users limited visibility into why certain posts are recommended. Meta says these new controls are designed to give users more influence over their experience without requiring them to manually curate every account they follow.
The move comes as social media companies face increasing pressure from regulators and users to make recommendation systems more transparent. Giving people more control over algorithmic content has become a growing trend across the industry, with platforms exploring ways to balance personalization, discovery, and user choice.
For creators, the update could also change how content reaches audiences. If users actively customize their recommendations, creators may need to produce more relevant and engaging content rather than relying solely on the platform's algorithm to boost visibility.
Although the feature is currently being tested with a limited group of users, it reflects Meta's broader strategy of making Instagram's recommendation system more flexible. The company has not announced when the feature will become available globally, but user feedback during testing will likely influence its final design.
As competition between social media platforms continues to intensify, giving users more control over their feeds may become an important differentiator. Rather than replacing the recommendation algorithm, Instagram aims to make it more responsive to individual preferences while maintaining personalized content discovery.