You are picturing Facebook employing enough people that they can investigate each flag personally for 15 minutes before making a decision?
Nearly every person you know would have to work for Facebook.
As you point out, making decisions about what people should and should not be allowed to say at the scale Facebook is attempting would require an impractical workforce.
There is absolutely no way Facebook's approach to communication is scalable. It's not financially viable. It's not ethically viable. It's not morally viable. It's not legally viable.
It's not just a Facebook problem. Many platforms for social communication aren't really viable at the scale they're trying to operate.
I'm skeptical that a global-scale AI working in the shadows is going to be a viable solution here. Each user, and each community's, definition of "desired moderation" is different.
As open-source AI improves, my hope is we start seeing LLMs capable of being trained against your personal moderation actions on an ongoing basis. Your LLM decides what content you want to see, and what content you don't. And, instead of it just "disappearing" when your LLM assistant moderates it, the content is hidden but still available for you to review and correct its moderation decisions.
I can't say it's the case for OPs case specifically, but I absolutely saw code that automatically closed tickets in a specific queue after a random(15-75) minutes to avoid being consistent with the close time so it wouldn't look too suspicious or automated to users.
If they actually took the effort to investigate as needed? It would take them even more.
Expecting them to actually sit and watch the video and understand meme/joke talk (or take you at face value when you say it's fine)? That's, like, crazy talk.
Whatever size the team is, they have millions of flagged messages to go through every day, and hundreds of thousands of appeals. If most of that wasn't automated or done as quickly and summarily as possible, they'd never do it.
But this implies that people at facebook believe so much in their AI that there is no way at all to appeal what it does to a human eventually. Not even for doing learning reinforcement they have human people to review eventually some post that a person keep saying the AI is flagging incorrectly.
Either they trust too much in the AI or they are incompetent.
No, it means that management has decided that the cost of assuring human review isn't worth the benefit. That doesn't mean they trust the AI particularly, it could just mean that they don’t see avoid false positives on detecting unwanted content as worth much cost to avoid.
Not caring at all about false positives, which by the way are very common, enters the category of incompetence for me.
Misalignment of Meta's interests with yours, not incompetence.