Yes. A detection system can be used to limit occurrences of this issue.
In this case, an issue with the detection system used on Facebook was demonstrated by a 20% failure rate.
Identifying themes in video is harder than natural language. But fundamentally it requires the same kind of ML tools as natural language, which these companies have already mastered. I think the bigger issue is that Facebook doesn't have a business purpose for understanding video as compelling as it has for understanding natural language. They also don't have a business purpose for building scalable content censoring workflows since there's no serious regulation.
But can an algorithm recognize that a video is of someone committing a real-life atrocity? Those are comparatively rare.
When you literally have thousands of humans all determined to bypass these detection systems by modifying the video and disguising it in various ways some of them are inevitably going to slip through. Is that really an issue with the detection system, or is there something wrong with the people who repeatedly try and upload and share videos of mass shootings?