Facebook wants users to have more say in what appears on their screens. But how much control do they actually have?
Meta has published a detailed explanation of its Facebook Your Algorithm controls, revealing how artificial intelligence processes user preferences and adjusts recommendations across Facebook Feed and Reels.
The November 10, 2026, engineering update provides a closer look at the feature introduced in October. Users can add topics they enjoy, reduce unwanted recommendations, and describe their interests using everyday language.
The technology goes beyond simple content filtering. Meta uses large language models, ranking adjustments, and real-time recommendation updates to respond when someone changes their preferences.
One detail stands out. Users can ask Facebook to show fewer AI-generated posts, although the platform doesn’t promise to remove them entirely.
Meta Explains How Facebook Your Algorithm Controls Work
Facebook’s Your Algorithm feature allows users to review and modify the interests that influence their content recommendations. The platform automatically generates an interest profile based on previous activity, including videos watched, posts viewed, and other engagement signals.
The interface organizes those preferences into two sections: Interested In and Not Interested In. Users can move topics between the lists, remove existing interests, or add new subjects using natural language.
Meta also provides a short summary of recent viewing interests, giving people an idea of how Facebook interprets their activity.
These preferences influence recommendations across both Feed and Reels. When users make changes, Facebook’s ranking system adjusts the content it considers relevant.
The company says its goal is to make personalization more responsive without requiring people to repeatedly interact with posts before the algorithm recognizes their preferences.
Facebook Gives Newly Added Interests a Temporary Ranking Boost
One of the more revealing details involves what happens when someone adds a new interest.
Meta says Facebook temporarily increases the ranking weight of newly selected topics so users can notice changes in their recommendations.
For example, someone who adds artificial intelligence or digital marketing to their interests may begin seeing more posts about those subjects.
The system searches for matching content and gives relevant recommendations additional consideration during ranking.
That extra visibility doesn’t continue indefinitely. After the initial period, Facebook returns to evaluating those topics using normal engagement signals.
If users continue watching and interacting with related posts, those activities can influence future recommendations. If they lose interest, the algorithm may gradually adjust.
Meta also limits how frequently recommendations about a single topic appear, preventing newly selected interests from dominating the entire feed.
The approach gives users a chance to explore new subjects without turning Facebook into a stream of nearly identical posts.
Meta Uses AI to Reduce Unwanted Content in Facebook Feeds
Facebook’s Not Interested In controls work differently from the system that promotes preferred topics.
When someone identifies an unwanted subject, Meta applies filtering and ranking adjustments at several stages of its recommendation process.
The system compares recommended posts against the user’s stated preferences and attempts to remove content that closely matches unwanted topics.
Other posts may receive lower rankings rather than disappearing completely.
Meta says this layered approach helps reduce unwanted recommendations while accounting for the difficulty of identifying content that may relate to several subjects.
The distinction matters because a single post can contain multiple themes. A technology video, for example, might discuss artificial intelligence, business, and social media simultaneously.
Facebook’s recommendation system must determine whether that content conflicts with the user’s preferences before deciding how prominently to display it.
Facebook Users Can Request Fewer AI-Generated Posts
Meta has confirmed that Your Algorithm can also respond to requests involving broader content characteristics, including AI-generated material.
Users who want fewer AI-generated posts can express that preference through the feature.
Instead of treating AI-generated content as a conventional topic, Facebook applies specialized ranking signals designed to reduce its visibility.
The same method can apply to sexually suggestive content.
These signals lower the priority of matching recommendations, but they don’t guarantee complete removal.
Some AI-generated images or videos may still appear, particularly when Facebook’s systems fail to identify them or other ranking factors influence the results.
For users frustrated by repetitive AI-generated content, the controls provide another way to influence their experience.
Still, Meta’s explanation makes clear that reducing content and blocking it entirely are two different things.
Facebook Can Filter Posts From Specific Creators
The updated system also allows users to express preferences involving individual content creators.
Meta says requests to avoid a particular creator can trigger direct filtering of that creator’s content.
This differs from the broader ranking adjustments Facebook uses for unwanted topics.
Someone might enjoy technology news but prefer not to receive recommendations from a particular account. The system can respond to that preference without removing technology-related content altogether.
This gives users a more targeted way to shape their feeds.
For creators and publishers, it also reinforces the importance of maintaining audience interest.
Users who repeatedly encounter unwanted posts may now have more direct ways to prevent recommendations from certain accounts.
Meta hasn’t announced new penalties for creators under Your Algorithm, but the feature gives audiences another mechanism for influencing which accounts appear in their recommendations.
Large Language Models Help Facebook Understand User Preferences
Meta’s explanation highlights the role of large language models in making algorithm customization possible.
Facebook uses these AI models to translate activity signals into recognizable interest categories.
Instead of showing users technical ranking information, the system creates understandable topic names based on what they have previously watched and interacted with.
Language models also review newly entered interests to determine whether they represent valid topics.
If someone adds a preference that closely resembles an existing interest, the system can recognize the overlap and organize it accordingly.
Once Facebook validates a preference, it converts the information into signals its recommendation system can use.
Meta also employs a specialized language model to review recommendations before displaying them, helping identify posts that conflict with recently expressed negative preferences.
The company says this additional check improves its ability to catch unwanted content that earlier filtering stages may have missed.
Meta Makes Facebook Algorithm Changes Respond More Quickly
Meta has also introduced technical adjustments intended to make preference changes visible sooner.
Ordinarily, Facebook prepares some recommendations before users actually see them. That creates a problem when someone updates their interests while content is already waiting to appear.
The new system addresses this through additional content requests and updates to temporarily stored recommendations.
When someone adds a topic, Facebook can retrieve fresh content outside its usual recommendation cycle.
When someone identifies an unwanted subject, the platform can remove matching recommendations that were already prepared for display.
These changes help Facebook respond more quickly without waiting for a complete feed refresh.
However, Meta hasn’t promised that every adjustment will produce perfect results.
The company acknowledges that interpreting ambiguous instructions and improving recommendation accuracy remain ongoing challenges.
Meta Faces Growing Pressure Over Algorithm-Driven Social Media Feeds
Facebook’s latest controls arrive as social media algorithms face renewed scrutiny over how they influence online experiences.
Platforms have spent years developing recommendation systems that prioritize content based on predicted user interest.
These systems can help people discover relevant posts, but they also raise questions about transparency and how much control users actually have.
Social Media Today reported that Australian authorities began preliminary investigations in October 2026 into possible rules requiring platforms to offer non-algorithmic feeds.
Such proposals could eventually challenge the default recommendation systems used by major social media companies.
Meta has a commercial reason to preserve personalized ranking.
During its second-quarter 2026 earnings discussion, the company reported that Facebook video viewing time had increased by 9% globally, largely because of improvements to Feed and Reels recommendations.
Giving users more customization options could help Meta address concerns about unwanted content while keeping its recommendation technology in place.
The important distinction is that Your Algorithm doesn’t disable Facebook’s ranking system. It allows people to influence how that system operates.
What Facebook’s Algorithm Controls Mean for Creators and Businesses
For content creators, publishers, and businesses, the changes introduce another factor that could influence how audiences discover posts.
Facebook already evaluates engagement, content relevance, and user behaviour when recommending material.
Your Algorithm adds more explicit information about what people want to see.
Someone interested in social media marketing, for example, could ask Facebook to recommend more posts covering advertising strategies, platform updates, and creator tools.
That may improve the chances of relevant content reaching interested viewers, although Meta hasn’t promised increased organic reach for creators.
The temporary ranking boost for new interests also means that any initial increase in visibility may not last.
Creators still need to produce material that encourages genuine engagement if they want audiences to continue seeing their posts.
For brands, the development highlights the value of publishing content that matches specific audience interests rather than relying entirely on attention-grabbing formats.
Facebook’s algorithm remains responsible for ranking recommendations, but users now have more opportunities to influence which subjects and creators receive their attention.
Facebook’s Your Algorithm Controls Offer More Choice Without Removing AI Ranking
Meta’s technical explanation makes one thing clear: Facebook is changing how users interact with its recommendation system, not abandoning algorithm-driven feeds.
The platform now combines user activity, direct instructions, large language models, and several layers of filtering to determine which content appears.
People can add new interests, reduce unwanted topics, and request fewer posts with certain characteristics.
Some adjustments take effect quickly, while others continue evolving based on future engagement.
Meta is also exploring additional ways for users to manage preferences throughout Facebook.
Whether these tools significantly improve the browsing experience will depend on how accurately the system interprets requests and whether people take the time to use them.
For now, Facebook users have a more direct way to tell the algorithm what they want.
The bigger question is whether having that option will be enough for people who want greater control over their social media feeds.
Sources
- Social Media Today – Meta Publishes Explainer on Your Algorithm Controls — November 11, 2026.
- Engineering at Meta – Your Algorithm: Giving People More Ways to Personalize Facebook Recommendations — November 10, 2026.
- Meta Newsroom – Your Algorithm, Your Words: New Ways to Shape What You See on Facebook — October 13, 2026.
