Instagram is expanding its efforts to give users greater influence over the content they see, introducing a series of experimental features designed to make its recommendation system more transparent and customizable. The changes build on the platform’s existing “Your Algorithm” controls and reflect growing public interest in how social media platforms shape user experiences.
While the new tools could help people fine-tune their feeds, some critics argue they still fall short of addressing one of users’ most common requests: the ability to see content primarily from accounts they choose to follow.
Instagram Expands “Your Algorithm” Features
Instagram chief Adam Mosseri recently outlined several new experiments aimed at making the platform’s recommendation controls more visible and easier to use.
According to Mosseri, Instagram wants to make the “Your Algorithm” feature feel more integrated throughout the app.
“We’re working on making Your Algorithm feel more present and useful across Instagram,” Mosseri said. “Some of this is testing now, some is coming soon, some might not work.”
The company is currently evaluating several ways to simplify access to recommendation settings and encourage users to actively shape what appears in their feeds.
Easier Access From the Home Screen
One proposed feature would allow users to pull down from the home screen to open the “Your Algorithm” panel.
From there, users could review and manage topics Instagram has associated with their interests based on engagement patterns such as likes, comments, views, and interactions. Topics could be added or removed to better reflect personal preferences.
Recommendation Controls Within Reels
Instagram is also exploring the possibility of placing recommendation controls directly within the Reels experience.
Under the concept being tested, users could access topic preferences between videos or through additional controls in the lower navigation area. This would make it easier to indicate whether they are interested in certain content categories without leaving the feed.
The goal is to create more immediate feedback loops between users and Instagram’s recommendation system.
Conversational Feedback for Feed Personalization
Another experiment involves conversational prompts that would allow users to communicate preferences in a more natural way.
Instead of manually adjusting topic settings, users could provide feedback through prompts designed to help Instagram better understand what they want to see.
Mosseri said the long-term vision is to make the algorithm feel less like an invisible system operating in the background and more like an interactive tool users can engage with directly.
As artificial intelligence capabilities improve, platforms like Instagram are increasingly able to interpret a wider range of user signals, potentially allowing for more personalized recommendations.
User Demands Go Beyond Algorithm Controls
Despite the new features, many Instagram users continue to call for a simpler solution: a feed that prioritizes content from accounts they intentionally follow.
That request has surfaced repeatedly across social media platforms in recent years. However, companies including Meta have largely continued to emphasize algorithm-driven feeds because they tend to generate higher engagement and longer user sessions.
For many users, the debate centers on the balance between personalization and control. While Instagram’s new tools provide additional ways to influence recommendations, they do not fundamentally change how content is selected and prioritized.
Will Users Actually Use the Tools?
Another challenge is adoption.
History has shown that many users request greater control over privacy settings, security features, feed preferences, and recommendation systems, yet relatively few actively manage those settings once they become available.
For most people, convenience remains the priority. Rather than manually adjusting preferences, users often prefer platforms that automatically learn from their behavior and continuously refine recommendations.
The success of short-form video platforms such as TikTok has reinforced this trend. Highly responsive recommendation algorithms have conditioned many users to expect personalized content without needing to customize settings themselves.
As a result, Instagram’s expanded controls may appeal most to power users who want more visibility into how recommendations work, while the broader user base continues to rely on automated personalization.
What the Changes Could Mean for Instagram
Making recommendation controls more prominent could increase awareness and usage of Instagram’s “Your Algorithm” tools. At the same time, questions remain about whether these features offer meaningful control or primarily serve to reassure users that they have influence over the platform’s content-selection process.
For Meta, the initiative may help address ongoing concerns about the role algorithms play in shaping online experiences. For users, the new tools represent another opportunity to personalize what appears in their feeds—at least in theory.
Whether these experiments become widely adopted features will likely depend on how useful users find them in practice and whether they deliver a noticeable improvement in content recommendations.
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