By: Ibraheem Muhammad Mustapha
Ever wondered why the news on your phone always seems to match your interests or opinions? It’s no coincidence. Every scroll, click, and pause you make is tracked, analyzed, and used by artificial intelligence (AI) to tailor your news feed. While that may sound helpful, it also raises some serious concerns about truth, transparency, and trust.
This article unpacks how AI personalizes your news, why that’s a problem, and what we can do to make things better.
What Is AI-Powered News Personalization?
News personalization is the use of AI algorithms to filter and recommend content that aligns with your preferences and behaviors. Social media platforms like Facebook, Twitter (now X), TikTok, and YouTube use these systems to decide what shows up on your feed. For instance, YouTube is tagged a master of getting you to watch videos you didn’t know existed minutes earlier. On an average day, people around the world watch one billion hours of video on YouTube. More than 70% of those videos are recommended by YouTube’s algorithms. News apps and websites also use AI to suggest articles based on your reading history.
These algorithms learn from your behavior—what you like, comment on, share, or even how long you hover over a post. The more data you feed them, the more they refine what they show you. The goal? Keep you engaged for as long as possible.
Why Personalized News Is a Problem
While personalized news seems convenient, it comes with hidden risks that affect both individuals and society as a whole.
1. Echo Chambers and Filter Bubbles
AI tends to show you more of what you already engage with. If you frequently read articles from a particular political viewpoint, the algorithm is likely to show you more of the same. This creates an echo chamber, where your beliefs are reinforced, not challenged.
Filter bubbles, a term popularized by internet activist Eli Pariser, refer to the invisible algorithmic walls that isolate you from opposing viewpoints. In short, you’re less likely to see diverse opinions or balanced news, and more likely to believe your view is the only valid one.
2. Spread of Misinformation
AI doesn’t distinguish between true and false information, it simply promotes what performs well. Unfortunately, false information often spreads faster and wider than the truth. A well-cited 2018 MIT study found that false news on Twitter was 70% more likely to be retweeted than true news, and it reached people six times faster.
In a personalized feed, viral misinformation can be repeatedly recommended, reinforcing false beliefs over time. During the COVID-19 pandemic, for instance, misleading claims about vaccines and cures spread quickly on platforms like YouTube and TikTok, partly due to algorithmic amplification. Concerns have also been raised about the use of deepfakes in the political sphere, with fake videos of world leaders being shared online during the Russia-Ukraine war.
3. Confirmation Bias and Polarization
Confirmation bias is the tendency to favor information that confirms our pre-existing beliefs. AI-fueled personalization feeds into this bias, showing content that makes users feel validated. Over time, this can increase political and ideological polarization, eroding trust in science, media, and even democracy.
Can We Fix It?
The good news is that several efforts are underway to address these issues. Tech companies, researchers, and governments are exploring solutions that balance personalization with truth and transparency.
1. Algorithmic Transparency
Some platforms are beginning to show users why a certain piece of content was recommended. This helps users understand the underlying logic of their feed—and question it when necessary. For instance, Meta platforms show users a “Why am I seeing this post?” option. When you click it, they explain why a certain ad, post, or suggestion appeared—based on your interests, past interactions, or demographics.
TikTok has also implemented a “Why this video” feature accessible through the share panel. This tool explains why a specific video was recommended, based on factors like user interactions and content popularity. Google’s “About this result” feature allows users to see why a particular search result was ranked, including information about the source and relevance to the search terms.
2. User Control
Tools that allow users to customize their feed settings, report misinformation, or access content from a wider range of sources are becoming more common. On Facebook, Users can adjust their News Feed preferences by selecting “Show more” or “Show less” on posts. This influences the algorithm to display more or fewer similar posts. Additionally, Facebook provides options to control who can comment on public posts and to report content that violates community standards. TikTok offers content controls, including a “Restricted Mode” to limit exposure to potentially inappropriate content. Users can also report videos, sounds, hashtags, or other content they find misleading or harmful. YouTube also allows users to customize their recommendations by marking videos as “Not interested” or by selecting “Don’t recommend channel.” Users can also report content that violates YouTube’s misinformation policies.
However, most people don’t use these tools—either because they’re hidden or too complex.
3. Fact-Checking and Partnerships
Collaborations between social media platforms and independent fact-checkers aim to flag or remove misleading content. Meta initiated its third-party fact-checking program in 2016, partnering with organizations certified by the International Fact-Checking Network (IFCN). These partners assess the accuracy of content, and when identified as false, such content is demoted in users’ feeds to reduce its spread. However, in early 2025, Meta announced the termination of this program in the U.S., replacing it with a crowd-sourced model called “Community Notes.” This shift has raised concerns about the effectiveness of combating misinformation without professional fact-checkers. TikTok collaborates with over 20 IFCN-accredited fact-checking organizations to review and assess the accuracy of content across its platform. In addition to these partnerships, TikTok is testing a new feature called “Footnotes,” allowing users to add context to videos, similar to community notes. This hybrid approach combines professional fact-checking with community contributions to address misinformation. X employs a crowd-sourced fact-checking system known as “Community Notes,” where users can add context to tweets. While this approach leverages community input, studies have shown that it may not effectively address the spread of misinformation, particularly during critical events like elections.
Still, challenges remain. A Reuters Digital News Report (2022) found that only 29% of users feel they understand how platforms recommend news content. That means the vast majority of users are unaware that what they’re seeing is algorithmically curated and potentially biased.
Final Thoughts
AI-driven news feeds aren’t inherently bad. They can help you discover relevant stories and stay informed on topics you care about. But when personalization comes at the cost of truth and diversity, it becomes a problem.
To reclaim control over your digital information diet, stay curious. Diversify your sources. Question the content that keeps showing up. And remember: just because something appears on your feed doesn’t mean it’s the full story, or even the true one.
