Mark Zuckerberg defends Meta’s shift in content moderation

Meta CEO Mark Zuckerberg has shared more details about the company’s recent decision to reduce fact-checking and shift to a Community Notes-style moderation model, similar to what is used on X (formerly Twitter). The change has sparked debate, with Zuckerberg defending the move as a response to user preferences and broader cultural trends.

As Zuckerberg explained, “People want to be able to discuss civic topics and make arguments that are in the mainstream of political discourse, etc. Some people may leave our platforms for virtue signaling, but I think the vast majority and many new users will find that these changes make the products better.”

However, this stance contradicts earlier statements from Meta. In 2021, Zuckerberg emphasised that users didn’t want politics to dominate their social media experience. The company subsequently reduced political content and praised the results, claiming it helped mitigate controversy and wasn’t a major driver of engagement.

Zuckerberg attributed the shift to what he called a ‘cultural tipping point’ following the latest U.S. election, where users showed renewed interest in political conversations. He also highlighted concerns about over-censorship, arguing that even a 1% error rate in content removal affects millions of users.

According to Zuckerberg, the Community Notes-style system will provide more context on a wider range of topics, with broader community input compared to traditional fact-checking.

While the concept has potential, Community Notes has faced challenges on X (formerly Twitter), such as delays due to cross-political agreement requirements and organised groups manipulating the system. These issues could be more pronounced given Meta’s larger scale.

On the other hand, publishers could benefit from this development since Meta will start recommending more civic content, which could boost reach and referral traffic. This comes after years of declining traffic for news publishers due to the platform deprioritising news content in its algorithms.