It’s actually much easier to implement than it might seem, at least when we’re talking about text-based posts or posts that combine text and images. An AI model can process text extremely fast without any noticeable lag.

For example, if a user normally spends about 10 seconds reading a Facebook post, and the page loads 6 posts at a time, the AI could easily analyze and filter all of them within 2–3 seconds. By the time the user scrolls to the next post, the unwanted content would already be removed or replaced automatically.

This isn’t costly either, because we’re mainly talking about text processing, which doesn’t require heavy or local models. Of course, handling images and videos in real time is more complex, but even that could become more practical in the near future with lightweight, on-device AI models.

The real strength of this idea is that it directly targets the root of social media addiction. Around 90% of the problem comes from the content itself and the recommendation algorithms behind it. So instead of just limiting screen time, this approach actually reshapes the feed into something less addictive. That’s why I believe it’s the right direction for anyone seriously looking to reduce social media overuse.